Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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they are not comprehensive nor are they the most current set.
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The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. through 2030. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). NEMS can be used to analyze the effects of existing and proposed government laws and regulations related to energy production and use; the potential impact of new and advanced energy production, conversion, and consumption technologies; the impact and cost of greenhouse gas control; the impact of increased use of renewable energy sources; and the potential savings from increased efficiency of energy use; and the impact of regulations on the use of alternative or reformulated fuels. NEMS has also been used for a number of special analyses at the request of the Administration, U.S. Congress, other offices of DOE and other government agencies, who specify the scenarios and assumptions for the analysis. Modules allow analyses to be conducted in energy topic areas such as residential demand, industrial demand, electricity market, oil and gas supply, renewable fuels, etc.

This report documents the objectives, analytical approach, and development of the National Energy ModelingSystem (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description ofthe NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in supportof its models (Public Law 94-385, section 57.b2). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

This report describes how Learning-by-Doing (LBD) is implemented endogenously in the National Energy ModelingSystem (NEMS) for generating plants. LBD is experiential learning that correlates to a generating technology's capacity growth. The annual amount of Learning-by-Doing affects the annual overnight cost reduction. Currently, there is no straightforward way to integrate and make sense of all the diffuse information related to the endogenous learning calculation in NEMS. This paper organizes the relevant information from the NEMS documentation, source code, input files, and output files, in order to make the model's logic more accessible. The end results are shown in three ways: in a simple spreadsheet containing all the parameters related to endogenous learning; by an algorithm that traces how the parameters lead to cost reductions; and by examples showing how AEO 2004 forecasts the reduction of overnight costs for generating technologies over time.

OVERVIEW OF NEMS OVERVIEW OF NEMS blueball.gif (205 bytes) Major Assumptions blueball.gif (205 bytes) NEMS Modular Structure blueball.gif (205 bytes) Integrating Module NEMS represents domestic energy markets by explicitly representing the economic decisionmaking involved in the production, conversion, and consumption of energy products. For example, the penetration of a new or advanced technology for electricity generation is projected only if the technology is deemed to be economic when considering the cost-minimizing mix of fuels over the life of the equipment. Since energy costs and availability and energy- consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to

NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. Since energy costs and availability and energy-consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to facilitate policy analysis and ensure the validity of the results. A summary of the detail provided in NEMS is shown below. Summary Table Major Assumptions Each module of NEMS embodies many assumptions and data to characterize the future production, conversion, or consumption of energy in the United States. Two major assumptions concern economic growth in the United States and world oil prices, as determined by world oil supply and demand.

The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2010) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMSsystem, the Industrial Model receives fuel prices, employment data, and the value of output of industrial activity. Based on the values of these variables, the Industrial Model passes back to the NEMSsystem estimates of consumption by fuel types.

The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994.

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
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The National Energy ModelingSystem (NEMS) is a computer modelingsystem that produces a general equilibrium solution for energy supply and demand in the US energy markets. The model achieves a supply and demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type such that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior. The NEMS Integrating Module is the central integrating component of a complex modelingsystem. As such, a thorough understanding of its role in the modeling process can only be achieved by placing it in the proper context with respect to the other modules. To that end, this document provides an overview of the complete NEMSmodel, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

The National Energy ModelingSystem (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

The National Energy ModelingSystem (NEMS) developed by the U.S. Department of Energy`s Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMSmodel does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated.

The micro/nanoelectromechanical systems (MEMS/NEMS) need to be designed to perform expected functions typically in millisecond to picosecond range. Expected life of the devices for high speed contacts can vary from few hundred thousand to many billions ... Keywords: MEMS, NEMS, Nanomaterials characterization, Nanomechanics, Nanotechnology

Because of exceptional mechanical, chemical, and tribological properties, diamond has a great potential to be used as a material for the development of high-performance MEMS and NEMS such as resonators and switches compatible with harsh environments, which involve mechanical motion and intermittent contact. Integration of such MEMS/NEMS devices with complementary metal oxide semiconductor (CMOS) microelectronics will provide a unique platform for CMOS-driven commercial MEMS/NEMS. The main hurdle to achieve diamond-CMOS integration is the relatively high substrate temperatures (600-800 C) required for depositing conventional diamond thin films, which are well above the CMOS operating thermal budget (400 C). Additionally, a materials integration strategy has to be developed to enable diamond-CMOS integration. Ultrananocrystalline diamond (UNCD), a novel material developed in thin film form at Argonne, is currently the only microwave plasma chemical vapor deposition (MPCVD) grown diamond film that can be grown at 400 C, and still retain exceptional mechanical, chemical, and tribological properties comparable to that of single crystal diamond. We have developed a process based on MPCVD to synthesize UNCD films on up to 200 mm in diameter CMOS wafers, which will open new avenues for the fabrication of monolithically integrated CMOS-driven MEMS/NEMS based on UNCD. UNCD films were grown successfully on individual Si-based CMOS chips and on 200 mm CMOS wafers at 400 C in a MPCVD system, using Ar-rich/CH4 gas mixture. The CMOS devices on the wafers were characterized before and after UNCD deposition. All devices were performing to specifications with very small degradation after UNCD deposition and processing. A threshold voltage degradation in the range of 0.08-0.44V and transconductance degradation in the range of 1.5-9% were observed.

2000 2000 (AEO2000) are generated from the National Energy ModelingSystem (NEMS), developed and main- tained by the Office of Integrated Analysis and Fore- casting of the Energy Information Administration (EIA). In addition to its use in the development of the AEO projections, NEMS is also used in analytical studies for the U.S. Congress and other offices within the Department of Energy. The AEO forecasts are also used by analysts and planners in other govern- ment agencies and outside organizations. The projections in NEMS are developed with the use of a market-based approach to energy analysis. For each fuel and consuming sector, NEMS balances the energy supply and demand, accounting for the eco- nomic competition between the various energy fuels and sources. The time horizon of NEMS is the mid- term period, approximately 20 years in the future. In order to represent the regional differences

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of US energy markets for the midterm period of 1990 to 2010. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system. The second chapter describes the modeling structure. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. Additional background on the development of the system is provided in Appendix A of this report, which describes the EIA modelingsystems that preceded NEMS. More detailed model documentation reports for all the NEMS modules are also available from EIA.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Provides an overview of the complete National Energy ModelingSystem (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

The National Energy ModelingSystem (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

The National Energy ModelingSystem (NEMS) is a comprehensive, computer-based, energy-economy modelingsystem developed and maintained by the Department of Energy's Energy Information Administration (EIA). NEMS forecasts the national production, imports, conversion, consumption, and prices of energy out to 2015, subject to macroeconomic assumptions, world energy markets, resource availability and costs, technological developments, and behavioral and technological choice criteria. NEMS has nine program modules of which the Commercial Sector Demand (CSD) module is one. Currently the CSD module uses a matrix of Energy Use Intensities (EUls) gleaned from the 1989 CBECS database to model service demand per major fuel type for eight different geographic census divisions and eleven different building types.

This memo explains what Berkeley Lab has learned about how the residential central air-conditioning (CAC) end use is represented in the National Energy ModelingSystem (NEMS). NEMS is an energy model maintained by the Energy Information Administration (EIA) that is routinely used in analysis of energy efficiency standards for residential appliances. As part of analyzing utility and environmental impacts related to the federal rulemaking for residential CAC, lower-than-expected peak utility results prompted Berkeley Lab to investigate the input load shapes that characterize the peaky CAC end use and the submodule that treats load demand response. Investigations enabled a through understanding of the methodology by which hourly load profiles are input to the model and how the model is structured to respond to peak demand. Notably, it was discovered that NEMS was using an October-peaking load shape to represent residential space cooling, which suppressed peak effects to levels lower than expected. An apparent scaling down of the annual load within the load-demand submodule was found, another significant suppressor of the peak impacts. EIA promptly responded to Berkeley Lab's discoveries by updating numerous load shapes for the AEO2002 version of NEMS; EIA is still studying the scaling issue. As a result of this work, it was concluded that Berkeley Lab's customary end-use decrement approach was the most defensible way for Berkeley Lab to perform the recent CAC utility impact analysis. This approach was applied in conjunction with the updated AEO2002 load shapes to perform last year's published rulemaking analysis. Berkeley Lab experimented with several alternative approaches, including modifying the CAC efficiency level, but determined that these did not sufficiently improve the robustness of the method or results to warrant their implementation. Work in this area will continue in preparation for upcoming rulemakings for the other peak coincident end uses, commercial air conditioning and distribution transformers.

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy ModelingSystem (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modelingsystems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis ModelingSystem (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.

National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). The National Energy ModelingSystem: An Overview presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, Â“BibliographyÂ”).

Overview of NEMS Overview of NEMS The National Energy ModelingSystem: An Overview 2003 Overview of NEMSNEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. Summary of NEMS Detail Table. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Figure 1. Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. Figure 2. National Energy ModelingSystem. Need help, contact the National Energy Information Center at 202-586-8800. Since energy costs and availability and energy-consuming characteristics

The National Energy ModelingSystem (NEMS) developed by the U.S. Department of Energy's Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMSmodel does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market Module of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated. MODELING OF BATTERY ENERGY STORAGE IN THE CONTENTS NATIONAL ENERGY MODELINGSYSTEM iv CONTENTS Acknowledgments Sandia National Laboratories (SNL) would like to acknowledge and thank Dr. Christine E. Platt of the U.S. Department of Energy's Office of Utility Technologies for the support and funding of this work. Thanks are also due to Paul C. Butler and Abbas A. Akhil...

The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of US energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors world energy markets, resource availability and costs, behavior and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. 21 figs.

Introduction Introduction The National Energy ModelingSystem: An Overview 2003 Introduction The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. energy markets for the midterm period through 2025. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). The National Energy ModelingSystem: An Overview 2003 presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, Â“BibliographyÂ”).

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy ModelingSystem (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy ModelingSystem (ITEMS), a model developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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This publication is on the WEB at: www.eia.doe.gov/oiaf/aeo/overview/index.html This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. PREFACE The National Energy ModelingSystem: An Overview provides a summary description of the National Energy ModelingSystem (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2020 for the Annual Energy Outlook 2000 (AEO2000), (DOE/EIA-0383(2000)), released in November 1999. AEO2000 presents national forecasts of energy markets for five cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document

INTRODUCTION INTRODUCTION blueball.gif (205 bytes) Purpose of NEMS blueball.gif (205 bytes) Representations of Energy Market blueball.gif (205 bytes) Technology Representation blueball.gif (205 bytes) External Availability The National Energy ModelingSystem (NEMS) is a computer-based, energy-economy modelingsystem of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S.

This report documents the objectives, analytical approach, and development of the National Energy ModelingSystem (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

Congestion analysis using National Energy Modeling National Energy ModelingSystem (NEMS) or NEMS-derivatives, such as LBNL-NEMS, is subject to significant caveats because the generation logic inherent in NEMS limits the extent to which interregional transmission can be utilized and intraregional transmission is not represented at all. The EMM is designed primarily to represent national energy markets therefore regional effects may be simplified in ways that make congestion analysis harder. Two ways in particular come to mind. First, NEMS underutilizes the capability of the traditional electric grid as it builds the dedicated and detached grid. Second, it also undervalues the costs of congestion by allowing more transmission than it should, due to its use of a transportation model rather than a transmission model. In order to evaluate benefits of reduced congestion using LBNL-NEMS, Berkeley Lab identified three possible solutions: (1) implement true simultaneous power flow, (2) always build new plants within EMM regions even to serve remote load, and (3) the dedicated and detached grid should be part of the known grid. Based on these findings, Berkeley Lab recommends the following next steps: (1) Change the build logic that always places new capacity where it is needed and allow the transmission grid to be expanded dynamically. (2) The dedicated and detached grid should be combined with the traditional grid. (3) Remove the bias towards gas fired combine cycle and coal generation, which are the only types of generation currently allowed out of region. (4) A power flow layer should be embedded in LBNL-NEMS to appropriately model and limit transmission.

This report documents the objectives, analaytical approach and design of the National Energy ModelingSystem (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy ModelingSystem (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modelingsystems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMSmodels. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy ModelingSystem`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

Each year, the U.S. Department of Energy's Energy Information Administration (EIA) publishes a forecast of the domestic energy economy in the Annual Energy Outlook (AEO). During the forecast period of the AEO (currently through 2020), renewable energy technologies have typically not achieved significant growth. The contribution of renewable technologies as electric generators becomes more important, however, in scenarios analyzing greenhouse gas emissions reductions or significant technological advancements. We examined the economic assumptions about wind power used for producing forecasts with the National Energy ModelingSystem (NEMS) to determine their influence on the projected capacity expansion of this technology. This analysis should help illustrate to policymakers what types of issues may affect wind development, and improve the general understanding of the NEMSmodel itself. Figure 1 illustrates the model structure and factors relevant to wind deployment. We found that NEMS uses various cost multipliers and constraints to represent potential physical and economic limitations to growth in wind capacity, such as resource depletion, costs associated with rapid manufacturing expansion, and grid stability with high levels of capacity from intermittent resources. The model's flexibility allows the user to make alternative assumptions about the magnitude of these factors. While these assumptions have little effect on the Reference Case forecast for the 1999 edition of the AEO, they can make a dramatic difference when wind is more attractive, such as under a carbon permit trading system. With $100/ton carbon permits, the wind capacity projection for 2020 ranges from 15 GW in the unaltered model (AEO99 Reference Case) to 168 GW in the extreme case when all the multipliers and constraints examined in this study are removed. Furthermore, if modifications are made to the model allowing inter-regional transmission of electricity, wind capacity is forecast to reach 214 GW when all limitations are removed. The figures in the upper end of these ranges are not intended to be viewed as reasonable projections, but their magnitude illustrates the importance of the parameters governing the growth of wind capacity and resource availability in forecasts using NEMS. In addition, many uncertainties exist regarding these assumptions that potentially affect the growth of wind power. We suggest several areas in which to focus future research in order to better model the potential development of this resource. Because many of the assumptions related to wind in the model are also used for other renewable technologies, these suggestions could be applied to other renewable resources as well.

This report describes Berkeley Lab's exploration of how the National Energy ModelingSystem (NEMS) models distributed generation (DG) and presents possible approaches for improving how DG is modeled. The on-site electric generation capability has been available since the AEO2000 version of NEMS. Berkeley Lab has previously completed research on distributed energy resources (DER) adoption at individual sites and has developed a DER Customer Adoption Model called DER-CAM. Given interest in this area, Berkeley Lab set out to understand how NEMSmodels small-scale on-site generation to assess how adequately DG is treated in NEMS, and to propose improvements or alternatives. The goal is to determine how well NEMSmodels the factors influencing DG adoption and to consider alternatives to the current approach. Most small-scale DG adoption takes place in the residential and commercial modules of NEMS. Investment in DG ultimately offsets purchases of electricity, which also eliminates the losses associated with transmission and distribution (T&D). If the DG technology that is chosen is photovoltaics (PV), NEMS assumes renewable energy consumption replaces the energy input to electric generators. If the DG technology is fuel consuming, consumption of fuel in the electric utility sector is replaced by residential or commercial fuel consumption. The waste heat generated from thermal technologies can be used to offset the water heating and space heating energy uses, but there is no thermally activated cooling capability. This study consists of a review of model documentation and a paper by EIA staff, a series of sensitivity runs performed by Berkeley Lab that exercise selected DG parameters in the AEO2002 version of NEMS, and a scoping effort of possible enhancements and alternatives to NEMS current DG capabilities. In general, the treatment of DG in NEMS is rudimentary. The penetration of DG is determined by an economic cash-flow analysis that determines adoption based on the n umber of years to a positive cash flow. Some important technologies, e.g. thermally activated cooling, are absent, and ceilings on DG adoption are determined by some what arbitrary caps on the number of buildings that can adopt DG. These caps are particularly severe for existing buildings, where the maximum penetration for any one technology is 0.25 percent. On the other hand, competition among technologies is not fully considered, and this may result in double-counting for certain applications. A series of sensitivity runs show greater penetration with net metering enhancements and aggressive tax credits and a more limited response to lowered DG technology costs. Discussion of alternatives to the current code is presented in Section 4. Alternatives or improvements to how DG is modeled in NEMS cover three basic areas: expanding on the existing total market for DG both by changing existing parameters in NEMS and by adding new capabilities, such as for missing technologies; enhancing the cash flow analysis but incorporating aspects of DG economics that are not currently represented, e.g. complex tariffs; and using an external geographic information system (GIS) driven analysis that can better and more intuitively identify niche markets.

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The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy ModelingSystem (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMSmodels. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.

Analysis and Representation of Miscellaneous Electric Loads in NEMS Analysis and Representation of Miscellaneous Electric Loads in NEMS Release date: January 6, 2014 Miscellaneous Electric Loads (MELs) comprise a growing portion of delivered energy consumption in residential and commercial buildings. Recently, the growth of MELs has offset some of the efficiency gains made through technology improvements and standards in major end uses such as space conditioning, lighting, and water heating. Miscellaneous end uses, including televisions, personal computers, security systems, data center servers, and many other devices, have continued to penetrate into building-related market segments. Part of this proliferation of devices and equipment can be attributed to increased service demand for entertainment, computing, and convenience appliances.

This report documents objectives and conceptual and methodological approach used in the development of the National Energy ModelingSystem (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1996 (AEO96). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s three submodules: Coal Production Submodule, Coal Export Submodule, and Coal Distribution Submodule.

The NEMS-MP model generates numerous results for each run of a scenario. (This model is the integrated National Energy ModelingSystem [NEMS] version used for the Multi-Path Transportation Futures Study [MP].) This appendix examines additional findings beyond the primary results reported in the Multi-Path Transportation Futures Study: Vehicle Characterization and Scenario Analyses (Reference 1). These additional results are provided in order to help further illuminate some of the primary results. Specifically discussed in this appendix are: (1) Energy use results for light vehicles (LVs), including details about the underlying total vehicle miles traveled (VMT), the average vehicle fuel economy, and the volumes of the different fuels used; (2) Resource fuels and their use in the production of ethanol, hydrogen (H{sub 2}), and electricity; (3) Ethanol use in the scenarios (i.e., the ethanol consumption in E85 vs. other blends, the percent of travel by flex fuel vehicles on E85, etc.); (4) Relative availability of E85 and H2 stations; (5) Fuel prices; (6) Vehicle prices; and (7) Consumer savings. These results are discussed as follows: (1) The three scenarios (Mixed, (P)HEV & Ethanol, and H2 Success) when assuming vehicle prices developed through literature review; (2) The three scenarios with vehicle prices that incorporate the achievement of the U.S. Department of Energy (DOE) program vehicle cost goals; (3) The three scenarios with 'literature review' vehicle prices, plus vehicle subsidies; and (4) The three scenarios with 'program goals' vehicle prices, plus vehicle subsidies. The four versions or cases of each scenario are referred to as: Literature Review No Subsidies, Program Goals No Subsidies, Literature Review with Subsidies, and Program Goals with Subsidies. Two additional points must be made here. First, none of the results presented for LVs in this section include Class 2B trucks. Results for this class are included occasionally in Reference 1. They represent a small, though noticeable, segment of the 'LV plus 2B' market (e.g., a little more than 3% of today's energy use in that market). We generally do not include them in this discussion, simply because it requires additional effort to combine the NEMS-MP results for them with the results for the other LVs. (Where there is an exception, we will indicate so.) Second, where reference is made to E85, the ethanol content is actually 74%. The Energy Information Administration (EIA) assumes that, to address cold-starting issues, the percent of ethanol in E85 will vary seasonally. The EIA uses an annual average ethanol content of 74% in its forecasts. That assumption is maintained in the NEMS-MP scenario runs.

Preface Preface The National Energy ModelingSystem: An Overview 2003 Preface The National Energy ModelingSystem: An Overview 2003 provides a summary description of the National Energy ModelingSystem (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2025 for the Annual Energy Outlook 2003 (AEO2003), (DOE/EIA-0383(2003)), released in January 2003. AEO2003 presents national forecasts of energy markets for five primary casesÂ—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

This report documents the objectives, analytical approach and development of the National Energy ModelingSystem (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMSsystem. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

The Natural Gas Transmission and Distribution Model (NGTDM) is a component of the National Energy ModelingSystem (NEMS) used to represent the domestic natural gas transmission and distribution system. NEMS is the third in a series of computer-based, midterm energy modelingsystems used since 1974 by the Energy Information Administration (EIA) and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. This report documents the archived version of NGTDM that was used to produce the natural gas forecasts used in support of the Annual Energy Outlook 1994, DOE/EIA-0383(94). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. It is intended to fulfill the legal obligation of the EIA to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). This report represents Volume 1 of a two-volume set. (Volume 2 will report on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.) Subsequent chapters of this report provide: (1) an overview of the NGTDM (Chapter 2); (2) a description of the interface between the National Energy ModelingSystem (NEMS) and the NGTDM (Chapter 3); (3) an overview of the solution methodology of the NGTDM (Chapter 4); (4) the solution methodology for the Annual Flow Module (Chapter 5); (5) the solution methodology for the Distributor Tariff Module (Chapter 6); (6) the solution methodology for the Capacity Expansion Module (Chapter 7); (7) the solution methodology for the Pipeline Tariff Module (Chapter 8); and (8) a description of model assumptions, inputs, and outputs (Chapter 9).

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Preface Preface The National Energy ModelingSystem: An Overview provides a summary description of the National Energy ModelingSystem (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2020 for the Annual Energy Outlook 2000 (AEO2000), (DOE/EIA-0383(2000)), released in November 1999. AEO2000 presents national forecasts of energy markets for five casesÂ—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

This paper describes a study of the national effects of widespread adoption of grid-connected residential rooftop photovoltaic (PV) systems. A Geographic Information System (GIS) model is used to estimate potential PV system adoption and PV electricity generation and the National Energy ModelingSystem (NEMS) is used to estimate the national effects of PV electricity generation. Adoption is assumed to occur if levelized PV system cost is less than the local average retail electricity rate at the country level. An estimate of the current {open_quotes}best{close_quotes} scenario (defined by a 6.5% real interest rate, 30-year loan life, $6{sub 1994}/W system cost, and $4{sub 1994}/month voluntary premium) results in no adoption. Several scenarios designed to stimulate PV adoption are modeled. As an example, if PV system costs are instead assumed to be $3{sub 1994}/W, rooftop systems are found to be cost effective in 16% of detached single-family households in the U.S. by 2015 (assuming full adoption of 4-kW systems), this results in 82.1 TWh of annual PV electricity generation, 170 TWh of avoided electricity transmission, distribution, and generation losses, 6 Mt/a of avoided carbon emissions, 50 kt/a of avoided NOx emissions, and 27.3 GW of avoided electricity generating capacity in place.

This report documents the objectives, analytical approach, and development of the National Energy ModelingSystem (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

6) 6) Distribution Category UC-950 The National Energy ModelingSystem: An Overview March 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or of any other organization. PREFACE The National Energy ModelingSystem: An Overview (Overview) provides a summary description of the National Energy ModelingSystem (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2015 for the Annual Energy Outlook 1996 (AEO96), (DOE/EIA- 0383(96)), released in January

This report documents the objectives, analytical approach, and design of the National Energy ModelingSystem (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

This report describes EIA's use of the National Energy ModelingSystem (NEMS) to evaluate the effects of the Administration's restructuring proposal using the parameter settings and assumptions from the Policy Office Electricity ModelingSystem (POEMS) analysis.

Macroeconomic Activity Module Macroeconomic Activity Module The National Energy ModelingSystem: An Overview 2003 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) links NEMS to the rest of the economy by providing projections of economic driver variables for use by the supply, demand, and conversion modules of NEMS. The derivation of the baseline macroeconomic forecast lays a foundation for the determination of the energy demand and supply forecast. MAM is used to present alternative macroeconomic growth cases to provide a range of uncertainty about the growth potential for the economy and its likely consequences for the energy system. MAM is also able to address the macroeconomic impacts associated with changing energy market conditions, such as alternative world oil price assumptions. Outside of the Annual Energy Outlook setting, MAM represents a system of linked modules which can assess the potential impacts on the economy of changes in energy events or policy proposals. These economic impacts then feed back into NEMS for an integrated solution. MAM consists of five modules:

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This is the fifth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy ModelingSystem (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1999.

This report documents the objectives, analytical approach, and design of the National Energy ModelingSystem (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

This report documents the objectives, analytical approach and development of the National Energy ModelingSystem (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. This document serves three purposes. First, it is a reference document providing a detailed description of TRAN for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, 57(b)(1)). Third, it permits continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

This report documents the objectives, analytical approach and development of the National Energy ModelingSystem (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

This report documents the objectives, analytical approach, and design of the National Energy ModelingSystem (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

Appendix E: Other NEMS-MP Results Appendix E: Other NEMS-MP Results for the Base Case and Scenarios Energy Systems Division Availability of This Report This report is available, at no cost, at http://www.osti.gov/bridge. It is also available on paper to the U.S. Department of Energy and its contractors, for a processing fee, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62

This is the fourth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy ModelingSystem (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1998. Since last year, severalnew end-use services were added to the module, including: Clothes washers,dishwashers, furnace fans, color televisions, and personal computers. Also, as with allNEMS modules, the forecast horizon has been extended to the year 2020.

3) 3) The National Energy ModelingSystem: An Overview 2003 March 2003 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. This publication is on the WEB at: www.eia.doe.gov/oiaf/aeo/overview/index.html The National Energy ModelingSystem: An Overview 2003 provides a summary description of the National En- ergy ModelingSystem (NEMS), which was used to generate the forecasts of energy production, demand, im- ports, and

residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMSsystem are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMSsystem are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. Figure 5. Residential Demand Module Structure RDM incorporates the effects of four broadly-defined determinants of energy consumption: economic and demographic effects, structural effects, technology turnover and advancement effects, and energy market effects. Economic and demographic effects include the number, dwelling type (single-family, multi-family or mobile homes), occupants per household, and location of housing units. Structural effects include increasing average dwelling size and changes in the mix of desired end-use services provided by energy (new end uses and/or increasing penetration of current end uses, such as the increasing popularity of electronic equipment and computers). Technology effects include changes in the stock of installed equipment caused by normal turnover of old, worn out equipment with newer versions which tend to be more energy efficient, the integrated effects of equipment and building shell (insulation level) in new construction, and in the projected availability of even more energy-efficient equipment in the future. Energy market effects include the short-run effects of energy prices on energy demands, the longer-run effects of energy prices on the efficiency of purchased equipment and the efficiency of building shells, and limitations on minimum levels of efficiency imposed by legislated efficiency standards.

This report documents the objectives, analytical approach and development of the National Energy ModelingSystem (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

This appendix discusses performance aspects of the Renewable Fuels Module (RFM). It is intended to present the pattern of response of the RFM to typical changes in its major inputs from other NEMS modules. The overall approach of this document, with the particular statistics presented, is designed to be comparable with similar analyses conducted for all of the modules of NEMS. While not always applicable, the overall approach has been to produce analyses and statistics that are as comparable as possible with model developer`s reports for other NEMS modules. Those areas where the analysis is somewhat limited or constrained are discussed. Because the RFM consists of independent submodules, this appendix is broken down by submodule.

This report documents the objectives, analytical approach, and development of the National Energy ModelingSystem (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

This report documents the objectives, analytical approach, and development of the National Energy ModelingSystem (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

The Macroeconomic Activity Module (MAM) serves two functions within the National Energy ModelingSystem (NEMS). First, it provides consistent sets of baselines macroeconomic variables (GDP and components, aggregate prices, interest rates, industrial output, housing starts, commercial floorspace, newcar sales, etc.) which are used by the supply, demand and conversion modules in reaching an energy market equilibrium. Second, it is designed to provide a feedback mechanism that alters the baseline variables during the course of an integrated NEMS run.

NEMSNEMS represents domestic energy markets by ex- plicitly representing the economic decision making involved in the production, conversion, and con- sumption of energy products. Where possible, NEMS includes explicit representation of energy technolo- gies and their characteristics. Since energy costs and availability and en- ergy-consuming characteristics can vary widely across regions, considerable regional detail is in- cluded. Other details of production and consumption cate- gories are represented to facilitate policy analysis and en- sure the validity of the results. A summary of the detail provided in NEMS is shown below. Major Assumptions Each module of NEMS embodies many assumptions and data to characterize the future production, conversion, or consumption of energy in the United States. Two major Energy Information Administration/The National Energy Modeling

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The National Energy ModelingSystem is documented in a series of model documentation reports, available on the EIA Web site at http://www.eia.doe. gov/bookshelf/docs.html or by contacting the National Energy Information Center (202/586-8800). The National Energy ModelingSystem is documented in a series of model documentation reports, available on the EIA Web site at http://www.eia.doe. gov/bookshelf/docs.html or by contacting the National Energy Information Center (202/586-8800). Energy Information Administration, Integrating Module of the National Energy ModelingSystem: Model Documentation DOE/EIA-M057(2000) (Washington, DC, December 1999). Energy Information Administration, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy ModelingSystem, DOE/EIA-M065(2000) (Washington, DC, December 1999). Energy Information Administration, Documentation of the DRI Model of the U.S. Economy, DOE/EIA- M061 (Washington, DC, December 1993). Energy Information Administration, NEMS International Energy Module: Model Documentation Report, DOE/EIA-M071(99) (Washington, DC, February 1999).

Technologically important nanomaterials come in all shapes and sizes. They can range from small molecules to complex composites and mixtures. Depending upon the spatial dimensions of the system and properties under investigation computer modeling of ... Keywords: DFT (density functional theory), Mesoscale modeling, Molecular modeling, NEGF (nonequilibrium Green's function), NEMS (nanoelectromechanical sensors), Nanocomposites, Nanotubes, Sensors

We present a hybrid nanoelectromechanical (NEM)/CMOS static random access memory (SRAM) cell, in which the two pull-down transistors of a conventional CMOS six transistor (6T) SRAM cell are replaced with NEM relays. This SRAM cell utilizes the infinite ...

LBNL-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Jesse A. Cohen, Jennifer L Efficiency and Renewable Energy, Office of Planning, Budget, and Analysis of the U.S. Department of Energy-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Prepared for the Office of Planning

During the last decade the use of numerical modeling for geothermal resource evaluation has grown significantly, and new modeling approaches have been developed. In this paper we present a summary of the present status in numerical modeling of geothermal systems, emphasizing recent developments. Different modeling approaches are described and their applicability discussed. The various modeling tasks, including natural-state, exploitation, injection, multi-component and subsidence modeling, are illustrated with geothermal field examples. 99 refs., 14 figs.

The coupled code TRAC-BF1/NEM is a thermal-hydraulic-neutronic code which allows transient simulations considering neutronic 3D and thermal-hydraulic process in multiple channels with one-dimensional geometry. TRAC-BF1 and NEM can be executed either in stand-alone mode, i.e. without coupling, as well as coupled. In stand-alone calculations NEM code is used without coupling and the thermal-hydraulic conditions (fuel temperature, moderator density and boron concentration) and xenon concentration for each node are taken from the SIMULATE3 output files. The NEM's source code has been modified to be able to read these conditions from external files when it is executed without being coupled. The coupling between TRAC-BF1 and NEM follows an integration scheme in which the thermal-hydraulic solution of TRAC-BF1 is sent to NEM to incorporate the feedback effects through the cross sections. TRAC-BF1 solves heat conduction equations inside of the heat structures using the 3D power distribution from NEM. The coupling is carried out through the communication protocol functions of PVM (Parallel Virtual Machine). The present article presents a study which constitutes an advance in the simulation of injection, transport and mix of boron in the reactor, increasing the capabilities of TRAC-BF1/NEM coupled code. This article shows the modifications introduced in the TRAC-BF1/NEM's source code to allow a more realistic simulation of boron injection transients. The qualification of these improvements in both codes is performed simulating a steady state of a generic BWR at nominal power. The results have been compared with SIMULATE3 which is used as a reference to obtain the cross sections through the SIMTAB methodology. (authors)

natural gas transmission and distribution module (NGTDM) of NEMS represents the natural gas market and determines regional market-clearing prices for natural gas supplies and for end-use consumption, given the information passed from other NEMS modules. A transmission and distribution network (Figure 15), composed of nodes and arcs, is used to simulate the interregional flow and pricing of gas in the contiguous United States and Canada in both the peak (December through March) and offpeak (April through November) period. This network is a simplified representation of the physical natural gas pipeline system and establishes the possible interregional flows and associated prices as gas moves from supply sources to end users. natural gas transmission and distribution module (NGTDM) of NEMS represents the natural gas market and determines regional market-clearing prices for natural gas supplies and for end-use consumption, given the information passed from other NEMS modules. A transmission and distribution network (Figure 15), composed of nodes and arcs, is used to simulate the interregional flow and pricing of gas in the contiguous United States and Canada in both the peak (December through March) and offpeak (April through November) period. This network is a simplified representation of the physical natural gas pipeline system and establishes the possible interregional flows and associated prices as gas moves from supply sources to end users. Figure 15. Natural Gas Transmission and Distribution Module Network

Macroeconomic assessment at EIA involves several modes of analysis. The first type of analysis, used in forecasting the Annual Energy Outlook where energy prices change, uses kernel regression and response surface techniques to mimic the response of larger macroeconomic and industrial models. This mode of analysis requires a given economic baseline and then calculates the economic impacts of changing energy prices, calculated from the chosen growth path. The economic growth cases are derived from the larger core models and can reflect either high, low, or reference case growth assumptions. Analyzing economic impacts from energy price changes uses the macroeconomic activity module (MAM) within NEMS and provides a subset of the macroeconomic variables available in the larger core models. The composition of the subset is determined by the other energy modules in NEMS, as they use various macroeconomic concepts as assumptions to their particular energy model.

Implementation of the Renewable Fuel Implementation of the Renewable Fuel Standard (RFS) in the Liquid Fuels Market Module (LFMM) of NEMS Michael H. Cole, PhD, PE michael.cole@eia.gov August 1, 2012 | Washington, DC LFMM / NEMS overview 2 M. Cole, EIA Advanced Biofuels Workshop August 1, 2012 | Washington, DC * LFMM is a mathematical representation of the U.S. liquid fuels market (motor gasoline, diesel, biofuels, etc.). EIA analysts use LFMM to project motor fuel prices and production approaches through 2040. * LFMM is a cost-minimization linear program (LP). For a given set of fuel demands, LFMM will find the least-cost means of satisfying those demands, subject to various constraints (such as the RFS). * LFMM is part of the National Energy ModelingSystem (NEMS), which is a computer model of the U.S. energy economy. EIA uses

Members of Congress have proposed a number of new aggressive plans for the reduction of greenhouse gases in the United States. Many of these proposals require reductions of 30% below current levels by 2020 and 60-80% reductions from current levels by 2050. While it is clear that achieving these proposed reductions will require major changes in U.S. energy infrastructure and technology implementation; it is only recently that quantitative analyses of the potential implications have become available. One of the critical questions to be addressed is the implications for various energy sources and technologies and the impact on energy prices to end users. This paper reports on the impacts of pending GHG legislation on energy supply, demand, and prices, and the technologies and market mechanisms that are likely to be employed to reduce CO2 emissions. The paper also reports on the results of analysis of GHG bills performed by SAIC using the National Energy ModelingSystem (NEMS). NEMS is an economy-wide, integrated energy model that analyzes energy supply, conversion, and demand. NEMS is used by the U.S. Energy Information Administration (EIA) to provide US energy market forecasts through 2030, and is the principal tool for the analysis of energy and greenhouse gas policies used by the U.S. government.

This updated directory has been published annually; after this issue, it will be published only biennially. The Disruption Impact Simulator Model in use by EIA is included. Model descriptions have been updated according to revised documentation approved during the past year. This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included are 37 EIA models active as of February 1, 1995. The first group is the National Energy ModelingSystem (NEMS) models. The second group is all other EIA models that are not part of NEMS. Appendix A identifies major EIA modelingsystems and the models within these systems. Appendix B is a summary of the `Annual Energy Outlook` Forecasting System.

Computational Physics Communication Networks and Technologies Modeling and Simulation Innovative Signal Processing Algorithms Advanced Control Systems Econometrics Engineering Analysis Behavioral Sciences Geographic Information Science and Technology Quantum Information Science Supercomputing and Computation Home | Science & Discovery | Supercomputing and Computation | Research Areas | SystemsModeling SHARE SystemsModelingSystemmodeling is the interdisciplinary study of the use of models to conceptualize and construct systems. A common type of systemsmodeling is function modeling, with specific techniques such as the functional flow block diagram. These models can be extended using functional decomposition, and can be linked to requirements models for further systems

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The 1990 Global Change Institute (GCI) on Earth SystemModeling is the third of a series organized by the Office for Interdisciplinary Earth Studies to look in depth at particular issues critical to developing a better understanding of the earth system. The 1990 GCI on Earth SystemModeling was organized around three themes: defining critical gaps in the knowledge of the earth system, developing simplified working models, and validating comprehensive systemmodels. This book is divided into three sections that reflect these themes. Each section begins with a set of background papers offering a brief tutorial on the subject, followed by working group reports developed during the institute. These reports summarize the joint ideas and recommendations of the participants and bring to bear the interdisciplinary perspective that imbued the institute. Since the conclusion of the 1990 Global Change Institute, research programs, nationally and internationally, have moved forward to implement a number of the recommendations made at the institute, and many of the participants have maintained collegial interactions to develop research projects addressing the needs identified during the two weeks in Snowmass.

This report documents the objectives, analytical approach, and design of the National Energy ModelingSystem (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

The use of linear statistical methods in building climate prediction models is examined, particularly the use of anomalies. The author’s perspective is that the climate system is a nonlinear interacting system, so the impact of modeling using ...

Coverage of system states during system testing is a nontrivial problem. It is because the number of system states is usually very large, and system developers often do not construct system state model. In this paper, we propose a method to design system ...

This directory contains descriptions about each model, including the title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included in this directory are 35 EIA models active as of May 1, 1993. Models that run on personal computers are identified by ``PC`` as part of the acronym. EIA is developing new models, a National Energy ModelingSystem (NEMS), and is making changes to existing models to include new technologies, environmental issues, conservation, and renewables, as well as extend forecast horizon. Other parts of the Department are involved in this modeling effort. A fully operational model is planned which will integrate completed segments of NEMS for its first official application--preparation of EIA`s Annual Energy Outlook 1994. Abstracts for the new models will be included in next year`s version of this directory.

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy ModelingSystem (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.

ABSTRACT. Claims that forest cutting (luring the last few decades has contributed significantly to the buildup in atmospheric CO2 have cast doubt on the validity of models used to estimate CO. uptake by the ocean. In this paper we review the existing models and conclude that the box-diffusion model of Oeschger and his co-workers provides an excellent fit to the average distributions of natural and bomb-produced radiocarbon. We also take the first steps toward a more detailed ocean model which takes into account upwelling in the equatorial zone and deep water formation in the polar zone. The model is calibrated using the distribution of bomb-produced and cosmic ray-produced radiocarbon in the ocean. Preliminary calculations indicate that the fossil fuel CO2 uptake by this model will be greater than that by the box-diffusion model of Oeschger and others (1975) but not great enough to accommodate a significant decline in the mass of the terrestrial biosphere over the past two decades.

Morgantown Energy Technology Center`s (METC) Process and Project Engineering (P&PE) personnel continue to refine and modify dynamic modeling or simulations for advanced power systems. P&PE, supported by Gilbert/Commonwealth, Inc. (G/C), has adapted PC/TRAX commercial dynamic software to include equipment found in advanced power systems. PC/TRAX`s software contains the equations that describe the operation of standard power plant equipment such as gas turbines, feedwater pumps, and steam turbines. The METC team has incorporated customized dynamic models using Advanced Continuous Simulation Language (ACSL) code for pressurized circulating fluidized-bed combustors, carbonizers, and other components that are found in Advanced Pressurized Fluidized-Bed Combustion (APFBC) systems. A dynamic model of a commercial-size APFBC power plant was constructed in order to determine representative operating characteristics of the plant and to gain some insight into the best type of control system design. The dynamic model contains both process and control model components. This presentation covers development of a model used to describe the commercial APFBC power plant. Results of exercising the model to simulate plant performance are described and illustrated. Information gained during the APFBC study was applied to a dynamic model of a 1-1/2 generation PFBC system. Some initial results from this study are also presented.

In this paper the idea of using Lindenmayer systems (L-systems) to create connectionist models is introduced. L-systems with some extensions provide us with a method for creating connectionist models with a close analogy to the growing process of nature. The main advantages to use L-systems in connectionist modeling is its capability for controling growth of connectionist model. Starting from a small initial state, the connectionist model is grown using a simple set of production rules. Learning is part of growth, where it can be implemented as a modification of connection parameter values or as a creation or deletion of connections themselves. The learning is implemented in the same way as growth was using internal production rules. A small scale example to use L-systems for the XOR problem is given. 1 Introduction In connectionist models knowledge is in the connections [20, page 132]. This implies that the connectionist modeling is knowledge representation modeling. In this paper we ...

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of ...

This directory revises and updates the 1993 directory and includes 15 models of the National Energy ModelingSystem (NEMS). Three other new models in use by the Energy Information Administration (EIA) have also been included: the Motor Gasoline Market Model (MGMM), Distillate Market Model (DMM), and the Propane Market Model (PPMM). This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses and requirements. Sources for additional information are identified. Included in this directory are 37 EIA models active as of February 1, 1994.

This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy ModelingSystem (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due in part to the presence of the squelch, a program algorithm designed to ensure changes in the system load over time are consistent with the input historic trend. The squelch applies a system load-scaling factor that scales any differences between the end-use bottom-up and system loads to maintain consistency with historic trends. To obtain more accurate peak reduction estimates, a new approach for modeling the impact of peaky end uses in NEMS-BT has been developed. The new approach decrements the system load directly, reducing the impact of the squelch on the final results. This report also discusses a number of additional factors, in particular non-coincidence between end-use loads and system loads as represented within NEMS, and their impacts on the peak reductions calculated by NEMS. Using Berkeley Lab's new double-decrement approach reduces the conservation load factor (CLF) on an input load decrement from 25% down to 19% for a SEER 13 CUAC trial standard level, as seen in NEMS-BT output. About 4 GW more in peak capacity reduction results from this new approach as compared to Berkeley Lab's traditional end-use decrement approach, which relied solely on lowering end use energy consumption. The new method has been fully implemented and tested in the Annual Energy Outlook 2003 (AEO2003) version of NEMS and will routinely be applied to future versions. This capability is now available for use in future end-use efficiency or other policy analysis that requires accurate representation of time varying load reductions.

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How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy ModelingSystem (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

Over the past year, several modifications have been made to the NEMS Transportation Model, incorporating greater levels of detail and analysis in modules previously represented in the aggregate or under a profusion of simplifying assumptions. This document is intended to amend those sections of the Model Documentation Report (MDR) which describe these superseded modules. Significant changes have been implemented in the LDV Fuel Economy Model, the Alternative Fuel Vehicle Model, the LDV Fleet Module, and the Highway Freight Model. The relevant sections of the MDR have been extracted from the original document, amended, and are presented in the following pages. A brief summary of the modifications follows: In the Fuel Economy Model, modifications have been made which permit the user to employ more optimistic assumptions about the commercial viability and impact of selected technological improvements. This model also explicitly calculates the fuel economy of an array of alternative fuel vehicles (AFV`s) which are subsequently used in the estimation of vehicle sales. In the Alternative Fuel Vehicle Model, the results of the Fuel Economy Model have been incorporated, and the program flows have been modified to reflect that fact. In the Light Duty Vehicle Fleet Module, the sales of vehicles to fleets of various size are endogenously calculated in order to provide a more detailed estimate of the impacts of EPACT legislation on the sales of AFV`s to fleets. In the Highway Freight Model, the previous aggregate estimation has been replaced by a detailed Freight Truck Stock Model, where travel patterns, efficiencies, and energy intensities are estimated by industrial grouping. Several appendices are provided at the end of this document, containing data tables and supplementary descriptions of the model development process which are not integral to an understanding of the overall model structure.

Hydrogen storage is recognized as a key technical hurdle that must be overcome for the realization of hydrogen powered vehicles. Metal hydrides and their doped variants have shown great promise as a storage material and significant advances have been made with this technology. In any practical storage system the rate of H2 uptake will be governed by all processes that affect the rate of mass transport through the bed and into the particles. These coupled processes include heat and mass transfer as well as chemical kinetics and equilibrium. However, with few exceptions, studies of metal hydrides have focused primarily on fundamental properties associated with hydrogen storage capacity and kinetics. A full understanding of the complex interplay of physical processes that occur during the charging and discharging of a practical storage system requires models that integrate the salient phenomena. For example, in the case of sodium alanate, the size of NaAlH4 crystals is on the order of 300nm and the size of polycrystalline particles may be approximately 10 times larger ({approx}3,000nm). For the bed volume to be as small as possible, it is necessary to densely pack the hydride particles. Even so, in packed beds composed of NaAlH{sub 4} particles alone, it has been observed that the void fraction is still approximately 50-60%. Because of the large void fraction and particle to particle thermal contact resistance, the thermal conductivity of the hydride is very low, on the order of 0.2 W/m-{sup o}C, Gross, Majzoub, Thomas and Sandrock [2002]. The chemical reaction for hydrogen loading is exothermic. Based on the data in Gross [2003], on the order of 10{sup 8}J of heat of is released for the uptake of 5 kg of H{sub 2}2 and complete conversion of NaH to NaAlH{sub 4}. Since the hydride reaction transitions from hydrogen loading to discharge at elevated temperatures, it is essential to control the temperature of the bed. However, the low thermal conductivity of the hydride makes it difficult to remove the heat of reaction, especially in the relatively short target refueling times, see Attachment 3. This document describes a detailed numerical model for general metal hydride beds that couples reaction kinetics with heat and mass transfer, for both hydriding and dehydriding of the bed. The detailed model is part of a comprehensive methodology for the design, evaluation and modification of hydrogen storage systems. In Hardy [2007], scoping models for reaction kinetics, bed geometry and heat removal parameters are discussed. The scoping models are used to perform a quick assessment of storage systems and identify those which have the potential to meet DOE performance targets. The operational characteristics of successful candidate systems are then evaluated with the more detailed models discussed in this document. The detailed analysis for hydrogen storage systems is modeled in either 2 or 3-dimensions, via the general purpose finite element solver COMSOL Multiphysics{reg_sign}. The two-dimensional model serves to provide rapid evaluation of bed configurations and physical processes, while the three-dimensional model, which requires a much longer run time, is used to investigate detailed effects that do not readily lend themselves to two-dimensional representations. The model is general and can be adapted to any geometry or storage media. In this document, the model is applied to a modified cylindrical shell and tube geometry with radial fins perpendicular to the axis, see Figures 4.1-1 and 4.1-2. Sodium alanate, NaAlH{sub 4}, is used as the hydrogen storage medium. The model can be run on any DOS, LINUX or Unix based system.

The Beam Characterization System (BCS) recently developed for heliostat evaluation at the Central Receiver Test Facility at Sandia Laboratories, measures, digitizes, records, and analyzes a flux-density pattern in a beam of reflected sunlight. Since the BCS collects data with a given set of conditions (geometry, weather, etc.) to determine optical specifications which can predict heliostat behavior under other sets of conditions, it is necessary to use a theoretical model of the system to interpret results. This model serves as an aid to define specifications, analyze measurements, calculate performance, and answer other questions about the heliostat. A statistical method is used to handle stochastic variables such as sun-tracking errors and surface-slope errors. A cone-optics technique is used to incorporate the statistics into a consistent model of the optical behavior of a heliostat. An overview of this model is given. Use of the model is unfolding slope-error distributions and sun-tracking statistics is described for measurements both in and out of the focal plane. The importance of auxiliary input information such as the sunshape (angular distribution of sun rays) to the analysis of BCS measurements is discussed. Finally, the role of the BCS in validating heliostats against acceptance criteria is summarized.

petroleum market module (PMM) represents domestic refinery operations and the marketing of petroleum products to consumption regions. PMM solves for petroleum product prices, crude oil and product import activity (in conjunction with the international energy module and the oil and gas supply module), and domestic refinery capacity expansion and fuel consumption. The solution is derived, satisfying the demand for petroleum products and incorporating the prices for raw material inputs and imported petroleum products, the costs of investment, and the domestic production of crude oil and natural gas liquids. The relationship of PMM to other NEMS modules is illustrated in Figure 17. petroleum market module (PMM) represents domestic refinery operations and the marketing of petroleum products to consumption regions. PMM solves for petroleum product prices, crude oil and product import activity (in conjunction with the international energy module and the oil and gas supply module), and domestic refinery capacity expansion and fuel consumption. The solution is derived, satisfying the demand for petroleum products and incorporating the prices for raw material inputs and imported petroleum products, the costs of investment, and the domestic production of crude oil and natural gas liquids. The relationship of PMM to other NEMS modules is illustrated in Figure 17. Figure 17. Petroleum Market Module Structure PMM is a regional, linear-programming representation of the U.S. petroleum market. Refining operations are represented by a three-region linear programming formulation of the five Petroleum Administration for Defense Districts (PADDs) (Figure 18). PADDs I and V are each treated as single regions, while PADDs II, III, and IV are aggregated into one region. Each region is considered as a single firm where more than 30 distinct refinery processes are modeled. Refining capacity is allowed to expand in each region, but the model does not distinguish between additions to existing refineries or the building of new facilities. Investment criteria are developed exogenously, although the decision to invest is endogenous.

Exascale supercomputers will have the potential for billion-way parallelism. While physical implementations of these systems are currently not available, HPC system designers can develop models of exascale systems to evaluate system design points. Modeling ... Keywords: exascale computing, parallel discrete-event simulation, storage system design

Integration of EBS Models with Generic Disposal SystemModels Integration of EBS Models with Generic Disposal SystemModels Integration of EBS Models with Generic Disposal SystemModels This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal systemmodel (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

Integration of EBS Models with Generic Disposal SystemModels Integration of EBS Models with Generic Disposal SystemModels Integration of EBS Models with Generic Disposal SystemModels This report summarizes research activities on engineered barrier system (EBS) model integration with the generic disposal systemmodel (GDSM), and used fuel degradation and radionuclide mobilization (RM) in support of the EBS evaluation and tool development within the Used Fuel Disposition campaign. This report addresses: predictive model capability for used nuclear fuel degradation based on electrochemical and thermodynamic principles, radiolysis model to evaluate the U(VI)-H2O-CO2 system, steps towards the evaluation of uranium alteration products, discussion of instant release fraction (IRF) of radionuclides from the nuclear fuel, and

The U.S. Department of Energy’s Fuel Cycle Technologies (FCT) Program is preparing to perform an evaluation of the full range of possible Nuclear Energy Systems (NES) in 2013. These include all practical combinations of fuels and transmuters (reactors and sub-critical systems) in single and multi-tier combinations of burners and breeders with no, partial, and full recycle. As part of this evaluation, Levelized Cost of Electricity at Equilibrium (LCAE) ranges for each representative system will be calculated. To facilitate the cost analyses, the 2009 Advanced Fuel Cycle Cost Basis Report is being amended to provide up-to-date cost data for each step in the fuel cycle, and a new analysis tool, NE-COST, has been developed. This paper explains the innovative “Island” approach used by NE-COST to streamline and simplify the economic analysis effort and provides examples of LCAE costs generated. The Island approach treats each transmuter (or target burner) and the associated fuel cycle facilities as a separate analysis module, allowing reuse of modules that appear frequently in the NES options list. For example, a number of options to be screened will include a once-through uranium oxide (UOX) fueled light water reactor (LWR). The UOX LWR may be standalone, or may be the first stage in a multi-stage system. Using the Island approach, the UOX LWR only needs to be modeled once and the module can then be reused on subsequent fuel cycles. NE-COST models the unit operations and life cycle costs associated with each step of the fuel cycle on each island. This includes three front-end options for supplying feedstock to fuel fabrication (mining/enrichment, reprocessing of used fuel from another island, and/or reprocessing of this island’s used fuel), along with the transmuter and back-end storage/disposal. Results of each island are combined based on the fractional energy generated by each islands in an equilibrium system. The cost analyses use the probability distributions of key parameters and employs Monte Carlo sampling to arrive at an island’s cost probability density function (PDF). When comparing two NES to determine delta cost, strongly correlated parameters can be cancelled out so that only the differences in the systems contribute to the relative cost PDFs. For example, one comparative analysis presented in the paper is a single stage LWR-UOX system versus a two-stage LWR-UOX to LWR-MOX system. In this case, the first stage of both systems is the same (but with different fractional energy generation), while the second stage of the UOX to MOX system uses the same type transmuter but the fuel type and feedstock sources are different. In this case, the cost difference between systems is driven by only the fuel cycle differences of the MOX stage.

In this work the performance of ensembles generated by commonly used methods in a nonlinear system with multiple attractors is examined. The model used here is a spectral truncation of a barotropic quasigeostrophic channel model. The system ...

Bounded model checking (BMC) is an attractive alternative to symbolic model checking, since it often allows a more efficient verification. The idea of BMC is to reduce the model checking problem to a satisfiability problem of the underlying base logic, ... Keywords: Bounded model checking, Global model checking, Infinite state systems, Local model checking, Temporal logic hierarchy

WSRC-TR-2007-00440, REVISION 0 WSRC-TR-2007-00440, REVISION 0 Keywords: Hydrogen Kinetics, Hydrogen Storage Vessel Metal Hydride Retention: Permanent Integrated Hydrogen Storage SystemModel Bruce J. Hardy November 16, 2007 Washington Savannah River Company Savannah River Site Aiken, SC 29808 Prepared for the U.S. Department of Energy Under Contract Number DEAC09-96-SR18500 DISCLAIMER This report was prepared for the United States Department of Energy under Contract No. DE-AC09-96SR18500 and is an account of work performed under that contract. Neither the United States Department of Energy, nor WSRC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for accuracy, completeness, or usefulness, of any information,

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The suite of concentrating solar power (CSP) modeling tools in NREL's System Advisor Model (SAM) includes technology performance models for parabolic troughs, power towers, and dish-Stirling systems. Each model provides the user with unique capabilities that are catered to typical design considerations seen in each technology. Since the scope of the various models is generally limited to common plant configurations, new CSP technologies, component geometries, and subsystem combinations can be difficult to model directly in the existing SAM technology models. To overcome the limitations imposed by representative CSP technology models, NREL has developed a 'Generic Solar System' (GSS) performance model for use in SAM. This paper discusses the formulation and performance considerations included in this model and verifies the model by comparing its results with more detailed models.

The Office of Integrated Analysis and Forecasting (OIAF) is required to provide complete model documentation to meet the EIA Model Acceptance Standards. The EIA Model Documentation: Petroleum Market Model of the National Energy ModelingSystem provides a complete description of the Petroleum Market Model`s (PMM) methodology, and relation to other modules in the National Energy ModelingSystem (NEMS). This Model Developer`s Report (MDR) serves as an appendix to the methodology documentation and provides an assessment of the sensitivity of PMM results to changes in input data. The MDR analysis for PMM is performed by varying several sets of input variables one-at-a-time and examining the effect on a set of selected output variables. The analysis is based on stand-alone, rather than integrated, National Energy ModelingSystem (NEMS) runs. This means that other NEMS modules are not responding to PMM outputs. The PMM models petroleum refining and marketing. The purpose of the PMM is to project petroleum product prices, refining activities, and movements of petroleum into the United States and among domestic regions. In addition, the PMM estimates capacity expansion and fuel consumption in, the refining industry. The PMM is also used to analyze a wide variety of petroleum-related issues and policies, in order to foster better understanding of the petroleum refining and marketing industry and the effects of certain policies and regulations. The PMM simulates the operation of petroleum refineries in the United States, including the supply and transportation of crude oil to refineries, the regional processing of these raw materials into petroleum products, and the distribution of petroleum products to meet regional demands. The essential outputs of this model are product prices, a petroleum supply/demand balance, demands for refinery fuel use, and capacity expansion.

The National Energy ModelingSystem (NEMS) is a computer modelingsystem developed by the Energy Information Administration (EIA). The NEMS produces integrated forecasts for energy markets in the United States by achieving a general equilibrium solution for energy supply and demand. Currently, for each year during the period from 1990 through 2010, the NEMS describes energy supply, conversion, consumption, and pricing. The Electricity Market Module (EMM) is the electricity supply component of the National Energy ModelingSystem (NEMS). The supply of electricity is a conversion activity since electricity is produced from other energy sources (e.g., fossil, nuclear, and renewable). The EMM represents the generation, transmission, and pricing of electricity. The EMM consists of four main submodules: Electricity Capacity Planning (ECP), Electricity Fuel Dispatching (EFD), Electricity Finance and Pricing (EFP), and Load and Demand-Side Management (LDSM). The ECP evaluates changes in the mix of generating capacity that are necessary to meet future demands for electricity and comply with environmental regulations. The EFD represents dispatching (i.e., operating) decisions and determines how to allocate available capacity to meet the current demand for electricity. Using investment expenditures from the ECP and operating costs from the EFD, the EFP calculates the price of electricity, accounting for state-level regulations involving the allocation of costs. The LDSM translates annual demands for electricity into distributions that describe hourly, seasonal, and time-of-day variations. These distributions are used by the EFD and the ECP to determine the quantity and types of generating capacity that are required to insure reliable and economical supplies of electricity. The EMM also represents nonutility suppliers and interregional and international transmission and trade. These activities are included in the EFD and the ECP.

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

The System Advisor Model (SAM) is free software developed by the National Renewable Energy Laboratory (NREL) for predicting the performance of renewable energy systems and analyzing the financial feasibility of residential, commercial, and utility-scale grid-connected projects. SAM offers several options for predicting the performance of photovoltaic (PV) systems. The model requires that the analyst choose from three PV systemmodels, and depending on that choice, possibly choose from three module and two inverter component models. To obtain meaningful results from SAM, the analyst must be aware of the differences between the model options and their applicability to different modeling scenarios. This paper presents an overview the different PV model options and presents a comparison of results for a 200-kW system using different model options.

This service report was undertaken at the February 2, 2004, request of Senator John Sununu to perform an assessment of the Conference Energy Bill of 2003. This report summarizes the CEB provisions that can be analyzed using the National Energy ModelingSystem (NEMS) and have the potential to affect energy consumption, supply, and prices. The impacts are estimated by comparing the projections with the CEB provisions to the AEO2004 Reference Case.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Macroeconomic Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) World Electricity Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Greenhouse Gases Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Natural Gas Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Main Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Coal Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) District Heat Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Commercial Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) International Transportation model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Residential Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) Refinery Model. It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

This report documents the objectives, analytical approach and development of the World Energy Projection System Plus (WEPS+) World Industrial Model (WIM). It also catalogues and describes critical assumptions, computational methodology, parameter estimation techniques, and model source code.

SnowModel is a spatially distributed snow-evolution modelingsystem designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, ...

Identification of nonlinear stochastic systems in the class of Hammerstein models is investigated with regard for the nonlinearities of the investigated object. Hammerstein models are constructed with regard for the output noise in the form of a martingale ...

The NCAR Climate SystemModel, version one, is described. The spinup procedure prior to a fully coupled integration is discussed. The fully coupled model has been run for 300 yr with no surface flux corrections in momentum, heat, or freshwater. ...

-0012) Vendor Prints 2) All equipments are modelled using the standard HYSYS unit operation models. 3) Butane BOG compressors with butane storage system is modelled for this report. 4) Modelling have been streams and out streams specifications for the butane storage tanks(T-1/2/3/4) with Butane BOG compressor

The mesoscale dispersion modelingsystem (MDMS) described herein is under development as a simulation tool to investigate atmospheric flow and pollution dispersion over complex terrain for domains up to several hundred kilometers. The system ...

Pipelining is a well understood and often used implementation technique for increasing the performance of a hardware system. We develop several SystemC/C++ modeling techniques that allow us to quickly model, simulate, and evaluate pipelines. We employ a small domain specific language (DSL) based on resource usage patterns that automates the drudgery of boilerplate code needed to configure connectivity in simulation models. The DSL is embedded directly in the host modeling language SystemC/C++. Additionally we develop several techniques for parameterizing a pipeline's behavior based on policies of function, communication, and timing (performance modeling).

Highlights: > Linking of models will provide a more complete, correct and credible picture of the systems. > The linking procedure is easy to perform and also leads to activation of project partners. > The simulation procedure is a bit more complicated and calls for the ability to run both models. - Abstract: Due to increased environmental awareness, planning and performance of waste management has become more and more complex. Therefore waste management has early been subject to different types of modelling. Another field with long experience of modelling and systems perspective is energy systems. The two modelling traditions have developed side by side, but so far there are very few attempts to combine them. Waste management systems can be linked together with energy systems through incineration plants. The models for waste management can be modelled on a quite detailed level whereas surrounding systems are modelled in a more simplistic way. This is a problem, as previous studies have shown that assumptions on the surrounding system often tend to be important for the conclusions. In this paper it is shown how two models, one for the district heating system (MARTES) and another one for the waste management system (ORWARE), can be linked together. The strengths and weaknesses with model linking are discussed when compared to simplistic assumptions on effects in the energy and waste management systems. It is concluded that the linking of models will provide a more complete, correct and credible picture of the consequences of different simultaneous changes in the systems. The linking procedure is easy to perform and also leads to activation of project partners. However, the simulation procedure is a bit more complicated and calls for the ability to run both models.

Turbo-expander systems have long been used instead of regulators, but they have recently received attention as a driving medium for power electrical generators. These systems typically replace the regulator valves that reduce the gas pressure in gas ... Keywords: dispersed generation, turbo-expander systems, variable nozzle angle

This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.

There are many simulation codes for accelerator modelling; each one has some strength but not all. A platform which can host multiple modelling tools would be ideal for various purposes. The model platform along with infrastructure support can be used not only for online applications but also for offline purposes. Collaboration is formed for the effort of providing such a platform. In order to achieve such a platform, a set of common physics data structure has to be set. Application Programming Interface (API) for physics applications should also be defined within a model data provider. A preliminary platform design and prototype is discussed.

Abstract. In this paper, we present an approach to define the semantics for object-oriented modeling languages. One important property of this semantics is to support underspecified and incomplete models. To this end, semantics is given as predicates over elements of the semantic domain. This domain is called the systemmodel which is a general declarative characterization of object systems. The systemmodel is very detailed since it captures various relevant structural, behavioral, and interaction aspects. This allows us to re-use the systemmodel as a domain for various kinds of object-oriented modeling languages. As a major consequence, the integration of language semantics is straight-forward. The whole approach is supported by tools that do not constrain the semantics definition’s expressiveness and flexibility while making it machinecheckable. 1

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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The System Advisor Model (SAM) is a free software tool that performs detailed analysis of both system performance and system financing for a variety of renewable energy technologies. This report provides detailed validation of the SAM flat plate photovoltaic performance model by comparing SAM-modeled PV system generation data to actual measured production data for nine PV systems ranging from 75 kW to greater than 25 MW in size. The results show strong agreement between SAM predictions and field data, with annualized prediction error below 3% for all fixed tilt cases and below 8% for all one axis tracked cases. The analysis concludes that snow cover and system outages are the primary sources of disagreement, and other deviations resulting from seasonal biases in the irradiation models and one axis tracking issues are discussed in detail.

Bifurcation Analysis of Various Power SystemModels William D. Rosehart Claudio A. Ca This paper presents the bifurcation analysis of a detailed power systemmodel composed of an aggregated induction motor and impedance load supplied by an under-load tap-changer transformer and an equivalent

To effectively manage the security or control of its borders, a country must understand its border management activities as a system. Using its systems engineering and security foundations as a Department of Energy National Security Laboratory, Sandia National Laboratories has developed such an approach to modeling and analyzing border management systems. This paper describes the basic model and its elements developed under Laboratory Directed Research and Development project 08-684.

A Laboratory-Directed Research and Development project was initiated in 2005 to investigate Human Performance Modeling in a System of Systems analytic environment. SAND2006-6569 and SAND2006-7911 document interim results from this effort; this report documents the final results. The problem is difficult because of the number of humans involved in a System of Systems environment and the generally poorly defined nature of the tasks that each human must perform. A two-pronged strategy was followed: one prong was to develop human models using a probability-based method similar to that first developed for relatively well-understood probability based performance modeling; another prong was to investigate more state-of-art human cognition models. The probability-based modeling resulted in a comprehensive addition of human-modeling capability to the existing SoSAT computer program. The cognitive modeling resulted in an increased understanding of what is necessary to incorporate cognition-based models to a System of Systems analytic environment.

The problem of describing variable structure models in a compact, object--oriented fashion is revisited and analyzed from the perspective of bond graph modeling. Traditionally, bond graphs have always been used to describe continuous-- time physical processes with a fixed structure. Yet, this paper shall demonstrate that bond graphs are equally suitable to describe variable structure models as fixed structure models. Moreover, a bond graph description of variable structure models can teach us a lot about the essential properties of variable structure models, properties that are not easily visible when other modeling approaches are taken. The paper discusses issues related to causality reassignment and conditional index changes as a consequence of switching in a physical system. Keywords: Bond graphs, variable structure system, computational causality, conditional index change, switching, object--oriented modeling, Dymola. INTRODUCTION When the causality strokes were added to the forme...

transportation demand module (TRAN) forecasts the consumption of transportation sector fuels by transportation mode, including the use of renewables and alternative fuels, subject to delivered prices of energy fuels and macroeconomic variables, including disposable personal income, gross domestic product, level of imports and exports, industrial output, new car and light truck sales, and population. The structure of the module is shown in Figure 8. transportation demand module (TRAN) forecasts the consumption of transportation sector fuels by transportation mode, including the use of renewables and alternative fuels, subject to delivered prices of energy fuels and macroeconomic variables, including disposable personal income, gross domestic product, level of imports and exports, industrial output, new car and light truck sales, and population. The structure of the module is shown in Figure 8. Figure 8. Transportation Demand Module Structure NEMS projections of future fuel prices influence the fuel efficiency, vehicle-miles traveled, and alternative-fuel vehicle (AFV) market penetration for the current fleet of vehicles. Alternative-fuel shares are projected on the basis of a multinomial logit vehicle attribute model, subject to State and Federal government mandates.

A new methodology for the object--oriented description of models consisting of a mixture of continuous and discrete components is presented. The object--oriented paradigm enables the user to describe such models in a modular fashion that permits the reuse of these models independently of the environment in which they are to be embedded. The paper explains the basic mechanisms needed for object--oriented modeling of hybrid systems by means of language constructs available in the object--oriented modeling language Dymola. It then addresses more advanced concepts such as variable structure models containing e.g. ideal electrical switches, ideal diodes and dry friction.

In all energy systems, the parameters necessary to calculate power are the same in functionality: an effort or force needed to create a movement in an object and a flow or rate at which the object moves. Therefore, the power equation can generalized as a function of these two parameters: effort and flow, P = effort * flow.
Analyzing various power transfer media this is true for at least three regimes: electrical, mechanical and hydraulic but not for magnetic. This implies that the conventional magnetic systemmodel (the reluctance model) requires modifications in order to be consistent with other energy systemmodels.
Even further, performing a comprehensive comparison among the systems, each system's model includes an effort quantity, a flow quantity and three passive elements used to establish the amount of energy that is stored or dissipated as heat. After evaluating each one of them, it was clear that the conventional magnetic model did not follow the same pattern: the reluctance, as analogous to the electric resistance, should be a dissipative element instead it is an energy storage element. Furthermore, the two other elements are not defined. This difference has initiated a reevaluation of the conventional magnetic model.
In this dissertation the fundamentals on electromagnetism and magnetic materials that supports the modifications proposed to the magnetic model are presented. Conceptual tests to a case study system were performed in order to figure out the network configuration that better represents its real behavior. Furthermore, analytical and numerical techniques were developed in MATLAB and Simulink in order to validate our model.
Finally, the feasibility of a novel concept denominated magnetic transmission line was developed. This concept was introduced as an alternative to transmit power. In this case, the media of transport was a magnetic material.
The richness of the power-invariant magnetic model and its similarities with the electric model enlighten us to apply concepts and calculation techniques new to the magnetic regime but common to the electric one, such as, net power, power factor, and efficiency, in order to evaluate the power transmission capabilities of a magnetic system.
The fundamental contribution of this research is that it presents an alternative to model magnetic systems using a simpler, more physical approach. As the model is standard to other systems' models it allows the engineer or researcher to perform analogies among systems in order to gather insights and a clearer understanding of magnetic systems which up to now has been very complex and theoretical.

The paper describes the design of a coloured Petri net model for a rather complex model train system. The purpose of this system is to teach graduate CS students net modelling and analysis techniques, and the systematic concersion of non--trivial net models into fully operational real systems. The track layout of this system currently includes three main cyclic tracks, each subdivided into several sections, three switchyards of several sidings, and also interconnecting tracks via which trains may change main tracks and directions. The idea is to equip each of several trains - currently up to ten - with its own travel plan. It specifies a sequence of tracks through which the train must be routed in the given order. Execution of these plans must be dynamically coordinated based on locally made decisions about the allocation of track sections to requesting trains so that essential safety and liveness properties are met. The paper first introduces the basic net components necessary to mod...

As cities evolve in size and complexity, their component systems become more interconnected. Comprehensive modeling and simulation is needed to capture interactions and correctly assess the impact of changes. This thesis ...

system, active surge control. A novel method of modeling centrifugal compression systems for surge control purposes by using bond graphs is presented. By using the bond graph method, we get a simple description of compression systems based on physical phenomena and it is straight forward to get the dynamic equations. It is demonstrated that several active surge control methods can be represented by the same bond graph. It is also shown how methods for active surge control can be classified using energy flow in terms of upstream energy injection or downstream energy dissipation. A model of a compression system with recycle flow is derived in this work. 1.

Formalizing linguists' intuitions of language change as a dynamical system, we quantify the time course of language change including sudden vs. gradual changes in languages. We apply the computer model to the historical ...

The Community Climate SystemModel, version 2 (CCSM2) is briefly described. A 1000-yr control simulation of the present day climate has been completed without flux adjustments. Minor modifications were made at year 350, which included all five ...

The fourth version of the Community Climate SystemModel (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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This paper introduces control system design based softwares, SIMNON and MATLAB/SIMULINK, for power electronics system simulation. A complete power electronics system typically consists of a rectifier bridge along with its smoothing capacitor, an inverter, and a motor. The system components, featuring discrete or continuous, linear or nonlinear, are modeled in mathematical equations. Inverter control methods,such as pulse-width-modulation and hysteresis current control, are expressed in either computer algorithms or digital circuits. After describing component models and control methods, computer programs are then developed for complete systems simulation. Simulation results are mainly used for studying system performances, such as input and output current harmonics, torque ripples, and speed responses. Key computer programs and simulation results are demonstrated for educational purposes.

The purpose of this study is to provide a detailed overview of photovoltaics (PV) performance modeling capabilities that have been developed during recent years for analyzing PV system and component design and policy issues. A set of 10 performance models have been selected which span a representative range of capabilities from generalized first-order calculations to highly specialized electrical network simulations. A set of performance modeling topics and characteristics is defined and used to examine some of the major issues associated with photovoltaic performance modeling. Next, each of the models is described in the context of these topics and characteristics to assess its purpose, approach, and level of detail. Then each of the issues is discussed in terms of the range of model capabilities available and summarized in tabular form for quick reference. Finally, the models are grouped into categories to illustrate their purposes and perspectives.

This project involves enhancement of the HWSIM distribution systemmodel to more accurately model pipe heat transfer. Recent laboratory testing efforts have indicated that the modeling of radiant heat transfer effects is needed to accurately characterize piping heat loss. An analytical methodology for integrating radiant heat transfer was implemented with HWSIM. Laboratory test data collected in another project was then used to validate the model for a variety of uninsulated and insulated pipe cases (copper, PEX, and CPVC). Results appear favorable, with typical deviations from lab results less than 8%.

In warm and humid climates, a primary source of building energy consumption is dehumidification of conditioned air supplied to the building spaces. The proposed system utilizes a selective membrane to remove water vapor from ambient air as opposed to a vapor compression cycle or a desiccant. This work provides an analysis of the membrane dehumidification system with a focus on the energy performance of the system. A system performance goal was set at the beginning for a given inlet and outlet ambient air condition and a total cooling load of one ton. The target COP of the combined sensible and latent cooling is 3.58 with a target value for only the latent system of 3.34. Two different simulations were developed including an initial simulation which uses a basic mass transfer model and a simpler condenser model. The initial model was used to develop the system, analyze operating parameters and provide initial performance results. The initial simulations indicate that the system requires two optimizations to meet the target performance: condenser pressure optimization and the use of multiple membrane segments operating at different pressures. The latent only COP including the optimizations was a maximum of 4.23. A second model was then developed which uses a more detailed mass transfer model and a more detailed condenser model based on the operating conditions. This simulation yielded a maximum latent only COP of 4.37 including the optimizations. The work also analyzes two different combined systems capable of providing both sensible and latent cooling. The first utilizes a conventional vapor compression cycle for sensible cooling and has a maximum COP of 3.93. The second uses multiple evaporative coolers in between multiple membrane dehumidification steps and was found to have a maximum COP of 3.73. Second law analysis of the systems was also conducted and found that the greatest reduction in latent system exergy loss can be obtained by improving the selectivity of the membrane. Apart from improving the membrane selectivity, the results show the greatest improvement can be found in improving the operation of the gas compression devices.

This report documents a series of models for describing intended and unintended discharges from liquid hydrogen storage systems. Typically these systems store hydrogen in the saturated state at approximately five to ten atmospheres. Some of models discussed here are equilibrium-based models that make use of the NIST thermodynamic models to specify the states of multiphase hydrogen and air-hydrogen mixtures. Two types of discharges are considered: slow leaks where hydrogen enters the ambient at atmospheric pressure and fast leaks where the hydrogen flow is usually choked and expands into the ambient through an underexpanded jet. In order to avoid the complexities of supersonic flow, a single Mach disk model is proposed for fast leaks that are choked. The velocity and state of hydrogen downstream of the Mach disk leads to a more tractable subsonic boundary condition. However, the hydrogen temperature exiting all leaks (fast or slow, from saturated liquid or saturated vapor) is approximately 20.4 K. At these temperatures, any entrained air would likely condense or even freeze leading to an air-hydrogen mixture that cannot be characterized by the REFPROP subroutines. For this reason a plug flow entrainment model is proposed to treat a short zone of initial entrainment and heating. The model predicts the quantity of entrained air required to bring the air-hydrogen mixture to a temperature of approximately 65 K at one atmosphere. At this temperature the mixture can be treated as a mixture of ideal gases and is much more amenable to modeling with Gaussian entrainment models and CFD codes. A Gaussian entrainment model is formulated to predict the trajectory and properties of a cold hydrogen jet leaking into ambient air. The model shows that similarity between two jets depends on the densimetric Froude number, density ratio and initial hydrogen concentration.

Complex embedded systems consist of hardware and software components from different domains, such as control and signal processing, many of them supplied by different IP vendors. The embedded system designer faces the challenge to integrate, optimize and verify the resulting heterogeneous systems. While formal verification is available for some subproblems, the analysis of the whole system is currently limited to simulation or emulation. In this paper, we tackle the analysis of global resource sharing, scheduling, and buffer sizing in heterogeneous embedded systems. For many practically used preemptive and non-preemptive hardware and software scheduling algorithms of processors and busses, semi-formal analysis techniques are known. However, they cannot be used in system level analysis due to incompatibilities of their underlying event models. This paper presents a technique to couple the analysis of local scheduling strategies via an event interface model. We derive transformation rules between the most important event models and provide proofs where necessary. We use expressive examples to illustrate their application.

A mathematical model describing the physical behavior of hot-water geothermal systems is presented. The model consists of a set of coupled partial differential equations for heat and mass transfer in porous media and an equation of state relating fluid density to temperature and pressure. The equations are solved numerically using an integrated finite difference method which can treat arbitrary nodal configurations in one, two, or three dimensions. The model is used to analyze cellular convection in permeable rock layers heated from below. Results for cases with constant fluid and rock properties are in good agreement with numerical and experimental results from other authors.

The U.S. Department of Energy (DOE) is interested in developing tools and methods for potential U.S. use in designing and evaluating safeguards systems used in enrichment facilities. This research focuses on analyzing the effectiveness of the safeguards in protecting against the range of safeguards concerns for enrichment plants, including diversion of attractive material and unauthorized modes of use. We developed an Extend simulation model for a generic medium-sized centrifuge enrichment plant. We modeled the material flow in normal operation, plant operational upset modes, and selected diversion scenarios, for selected safeguards systems. Simulation modeling is used to analyze both authorized and unauthorized use of a plant and the flow of safeguards information. Simulation tracks the movement of materials and isotopes, identifies the signatures of unauthorized use, tracks the flow and compilation of safeguards data, and evaluates the effectiveness of the safeguards system in detecting misuse signatures. The simulation model developed could be of use to the International Atomic Energy Agency IAEA, enabling the IAEA to observe and draw conclusions that uranium enrichment facilities are being used only within authorized limits for peaceful uses of nuclear energy. It will evaluate improved approaches to nonproliferation concerns, facilitating deployment of enhanced and cost-effective safeguards systems for an important part of the nuclear power fuel cycle.

Concerns about the difficulties in securing water have led the Australian coal mining industry to seek innovative ways to improve its water management and to adopt novel strategies that will lead to less water being used and more water being reused. ... Keywords: Mining, Sustainable development, Systemsmodel, Water balance, Water resources management

In some areas, wind power has reached a level where it begins to impact grid operation and the stability of local utilities. In this paper, the model development for a large wind farm will be presented. Wind farm dynamic behavior and contribution to stability during transmission system faults will be examined.

Evacuation Modeling Evacuation ModelingSystem (OREMS) Research Brief Oak Ridge National Laboratory managed by UT-Battelle, LLC for the U.S. Department of Energy under Contract number DE-AC05-00OR22725 Research Areas Freight Flows Passenger Flows Supply Chain Efficiency Transportation: Energy Environment Safety Security Vehicle Technologies T he vulnerability of communities to terrorist inflicted damage at facilities such as dams, power plants, or oil/gas distribution facilities, and others, is partly determined by the ability to avoid impacts. OREMS, or the Oak Ridge Evacuation ModelingSystem, is a Windows- based software program designed to analyze and evaluate large-scale vehicular emergency evacuations, conduct evacuation time estimation studies, and develop evacuation

Electricity generating companies and power system operators face the need to minimize total fuel cost or maximize total profit over a given time period. These issues become optimization problems subject to a large number of constraints that must be satisfied simultaneously. The grid updates due to smart-grid technologies plus the penetration of intermittent re- sources in electrical grid introduce additional complexity to the optimization problem. The Renewable Integration Model (RIM) is a computer model of interconnected power system. It is intended to provide insight and advice on complex power systems management, as well as answers to integration of renewable energy questions. This paper describes RIM basic design concept, solution method, and the initial suite of modules that it supports.

To partially fulfill the requirements for {open_quotes}Model Acceptance{close_quotes} as stipulated in EIA Standard 91-01-01 (effective February 3, 1991), the Office of Integrated Analysis and Forecasting has conducted tests of the Natural Gas Transmission and Distribution Model (NGTDM) for the specific purpose of validating the forecasting model. This volume of the model documentation presents the results of {open_quotes}one-at-a-time{close_quotes} sensitivity tests conducted in support of this validation effort. The test results are presented in the following forms: (1) Tables of important model outputs for the years 2000 and 2010 are presented with respect to change in each input from the reference case; (2) Tables of percent changes from base case results for the years 2000 and 2010 are presented for important model outputs; (3) Tables of conditional sensitivities (percent change in output/percent change in input) for the years 2000 and 2010 are presented for important model outputs; (4) Finally, graphs presenting the percent change from base case results for each year of the forecast period are presented for selected key outputs. To conduct the sensitivity tests, two main assumptions are made in order to test the performance characteristics of the model itself and facilitate the understanding of the effects of the changes in the key input variables to the model on the selected key output variables: (1) responses to the amount demanded do not occur since there are no feedbacks of inputs from other NEMSmodels in the stand-alone NGTDM run. (2) All the export and import quantities from and to Canada and Mexico, and liquefied natural gas (LNG) imports and exports are held fixed (i.e., there are no changes in imports and exports between the reference case and the sensitivity cases) throughout the forecast period.

This paper explores the recovery and rate capacity effect for batteries used in embedded systems. It describes the prominent battery models with their advantages and drawbacks. It then throws new light on the battery recovery behavior, which can help determine optimum discharge profiles and hence result in significant improvement in battery lifetime. Finally it proposes a fast and accurate stochastic model which draws the positives from the earlier models and minimizes the drawbacks. The parameters for this model are determined by a pretest, which takes into account the newfound background into recovery and rate capacity hence resulting in higher accuracy. Simulations conducted suggest close correspondence with experimental results and a maximum error of 2.65 %. 1.

An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating ... Keywords: Extended Kalman filter, Leaf area index and soil moisture model, Nonlinear environmental system, Particle filter, State and parameter estimation, Variational filter

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Physical or virtual models are commonly used to visualize the conceptual ideas of architects, lighting designers and researchers; they are also employed to assess the daylighting performance of buildings, particularly in cases where Complex Fenestration Systems (CFS) are considered. Recent studies have however revealed a general tendency of physical models to over-estimate this performance, compared to those of real buildings; these discrepancies can be attributed to several reasons. In order to identify the main error sources, a series of comparisons in-between a real building (a single office room within a test module) and the corresponding physical and virtual models was undertaken. The physical model was placed in outdoor conditions, which were strictly identical to those of the real building, as well as underneath a scanning sky simulator. The virtual model simulations were carried out by way of the Radiance program using the GenSky function; an alternative evaluation method, named Partial Daylight Factor method (PDF method), was also employed with the physical model together with sky luminance distributions acquired by a digital sky scanner during the monitoring of the real building. The overall daylighting performance of physical and virtual models were assessed and compared. The causes of discrepancies between the daylighting performance of the real building and the models were analysed. The main identified sources of errors are the reproduction of building details, the CFS modelling and the mocking-up of the geometrical and photometrical properties. To study the impact of these errors on daylighting performance assessment, computer simulation models created using the Radiance program were also used to carry out a sensitivity analysis of modelling errors. The study of the models showed that large discrepancies can occur in daylighting performance assessment. In case of improper mocking-up of the glazing for instance, relative divergences of 25-40% can be found in different room locations, suggesting that more light is entering than actually monitored in the real building. All these discrepancies can however be reduced by making an effort to carefully mock up the geometry and photometry of the real building. A synthesis is presented in this article which can be used as guidelines for daylighting designers to avoid or estimate errors during CFS daylighting performance assessment. (author)

Most system performance models assume a point measurement for irradiance and that, except for the impact of shading from nearby obstacles, incident irradiance is uniform across the array. Module temperature is also assumed to be uniform across the array. For small arrays and hourly-averaged simulations, this may be a reasonable assumption. Stein is conducting research to characterize variability in large systems and to develop models that can better accommodate large system factors. In large, multi-MW arrays, passing clouds may block sunlight from a portion of the array but never affect another portion. Figure 22 shows that two irradiance measurements at opposite ends of a multi-MW PV plant appear to have similar irradiance (left), but in fact the irradiance is not always the same (right). Module temperature may also vary across the array, with modules on the edges being cooler because they have greater wind exposure. Large arrays will also have long wire runs and will be subject to associated losses. Soiling patterns may also vary, with modules closer to the source of soiling, such as an agricultural field, receiving more dust load. One of the primary concerns associated with this effort is how to work with integrators to gain access to better and more comprehensive data for model development and validation.

The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA.

An investigation was conducted to assess the need for and the feasibility of developing a computer code that could model thermodynamic systems and predict the performance of energy conversion systems. To assess the market need for this code, representatives of a few industrial organizations were contacted, including manufacturers, system and component designers, and research personnel. Researchers and small manufacturers, designers, and installers were very interested in the possibility of using the proposed code. However, large companies were satisfied with the existing codes that they have developed for their own use. Also, a survey was conduced of available codes that could be used or possibly modified for the desired purpose. The codes were evaluated with respect to a list of desirable features, which was prepared as a result of the survey. A few publicly available codes were found that might be suitable. The development, verification, and maintenance of such a code would require a substantial, ongoing effort. 21 refs.

Screening, evaluation and optimization of the steam flooding process in homogeneous reservoirs can be performed by using simple analytical predictive models. In the absence of any analytical model for layered reservoirs, at present, only numerical simulators can be used. And these are expensive. In this study, an analytical model has been developed considering two isolated layers of differing permeabilities. The principle of equal flow potential is applied across the two layers. Gajdica`s (1990) single layer linear steam drive model is extended for the layered system. The formulation accounts for variation of heat loss area in the higher permeability layer, and the development of a hot liquid zone in the lower permeability layer. These calculations also account for effects of viscosity, density, fractional flow curves and pressure drops in the hot liquid zone. Steam injection rate variations in the layers are represented by time weighted average rates. For steam zone calculations, Yortsos and Gavalas`s (1981) upper bound method is used with a correction factor. The results of the model are compared with a numerical simulator. Comparable oil and water flow rates, and breakthrough times were achieved for 100 cp oil. Results with 10 cp and 1000 cp oils indicate the need to improve the formulation to properly handle differing oil viscosities.

Actor-based modeling has been successfully applied to the representation of concurrent and distributed systems. Besides having an appropriate and efficient way for modeling these systems, one needs a formal verification approach for ensuring their correctness. ... Keywords: actor model, compositional verification, model checking, property preserving abstraction, reactive systems

Four approaches to modeling multi-junction concentrating photovoltaic system performance are assessed by comparing modeled performance to measured performance. Measured weather, irradiance, and system performance data were collected on two systems over a one month period. Residual analysis is used to assess the models and to identify opportunities for model improvement.

When modeling a linear system in a parametric way, one needs to deal with (i) model structure selection, (ii) model order selection as well as (iii) an accurate fit of the model. The most popular model structure for linear systems has a rational form ... Keywords: Continuous-time modeling, Fractional order systems, Linear systems, Non-asymptotic, Nonlinear least squares, Parametric models, Poor frequency resolutions, Statistical signal processing, Transfer function

This report reviews user-oriented generalized reservoir/river systemmodels. The terms reservoir/river system, reservoir system, reservoir operation, or river basin management "model" or "modelingsystem" are used synonymously to refer to computer modelingsystems that simulate the storage, flow, and diversion of water in a system of reservoirs and river reaches. Generalized means that a computer modelingsystem is designed for application to a range of concerns dealing with river basin systems of various configurations and locations, rather than being site-specific customized to a particular system. User-oriented implies the modelingsystem is designed for use by professional practitioners (model-users) other than the original model developers and is thoroughly tested and well documented. User-oriented generalized modelingsystems should be convenient to obtain, understand, and use and should work correctly, completely, and efficiently.
Modeling applications often involve a system of several simulation models, utility software products, and databases used in combination. A reservoir/river systemmodel is itself a modelingsystem, which often serves as a component of a larger modelingsystem that may include watershed hydrology and river hydraulics models, water quality models, databases and various software tools for managing time series, spatial, and other types of data.
Reservoir/river systemmodels are based on volume-balance accounting procedures for tracking the movement of water through a system of reservoirs and river reaches. The model computes reservoir storage contents, evaporation, water supply withdrawals, hydroelectric energy generation, and river flows for specified system operating rules and input sequences of stream inflows and net evaporation rates. The hydrologic period-of-analysis and computational time step may vary greatly depending on the application. Storage and flow hydrograph ordinates for a flood event occurring over a few days may be determined at intervals of an hour or less. Water supply capabilities may be modeled with a monthly time step and several decade long period-of-analysis capturing the full range of fluctuating wet and dry periods including extended drought. Stream inflows are usually generated outside of the reservoir/river systemmodel and provided as input to the model. However, reservoir/river systemmodels may also include capabilities for modeling watershed precipitation-runoff processes to generate inflows to the river/reservoir system. Some reservoir/river systemmodels simulate water quality constituents along with water quantities. Some models include features for economic evaluation of system performance based on cost and benefit functions expressed as a function of flow and storage.

The VISION model has been developed by the U.S. Department of Energy (DOE) to provide estimates of the potential energy use, oil use, and carbon emission impacts to 2050 of advanced light- and heavy-duty highway vehicle technologies and alternative fuels. DOE supports research of advanced transportation technologies (including fuels) and is frequently asked to provide estimates of the potential impacts of successful market penetration of these technologies, sometimes on a relatively quick-turnaround basis. VISION is a spreadsheet model in Microsoft Excel that can be used to respond rapidly to quick-turnaround requests, as well as for longer-term analyses. It uses vehicle survival and age-dependent usage characteristics to project total light and heavy vehicle stock, total vehicle miles of travel (VMT), and total energy use by technology and fuel type by year, given market penetration and vehicle energy efficiency assumptions developed exogenously. Total carbon emissions for on-highway vehicles by year are also estimated because life-cycle carbon coefficients for various fuels are included in VISION. VISION is not a substitute for the transportation component of the Energy Information Administration's (EIA's) National Energy ModelingSystem (NEMS). NEMS incorporates a consumer choice model to project market penetration of advanced vehicles and alternative fuels. The projections are made within the context of the entire U.S. economy. However, the NEMSmodel is difficult to use on a quick-turnaround basis and only makes projections to 2025. VISION complements NEMS with its relative ''user-friendliness'' and by extending the time frame of potential analysis. VISION has been used for a wide variety of purposes. For illustration, we have listed some of its most recent and current uses in Table 1.1. Figures 1.1-1.3 illustrate the results of some of those runs. These graphs are not actual model output, but they are based on model results. The main body of this report describes VISION's methodology and data sources. The methodology and data sources used in the light- and heavy-vehicle portions of the model are discussed separately. Some suggestions for future improvements to the model are made. Appendix A provides instructions on how to run the VISION model. Appendix B describes the procedure for updating the model with the latest EIA Annual Energy Outlook (AEO).

Parallel file systems are significant challenges for high performance data-intensive system designers due to their complexity. Being able to study features and designs before building the actual system is an advantage that a simulation model can offer. ... Keywords: colored petri net, parallel file systemmodeling, parallel file system simulation, pvfs

This article tests two competing theories of system development referred to here as environmental and institutional models. These models form the basis for most explanations of why systems are developed and utilized. We will examine both models in detail ...

The Inverse Ocean Modeling (IOM) System is a modular system for constructing and running weak-constraint four-dimensional variational data assimilation (W4DVAR) for any linear or nonlinear functionally smooth dynamical model and observing array. ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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The Community Earth SystemModel (CESM) is a flexible and extensible community tool used to investigate a diverse set of Earth system interactions across multiple time and space scales. This global coupled model significantly extends its predecessor, the ...

Most agent-based simulation toolkits are based on the Java programming language. This makes their use difficult for social scientists, who are usually not skilled in computer programming. However, agent modelling concepts are not unlike those which ... Keywords: ABM, IDK, INGENIAS development kit, MAS, agent development tools, agent-based modelling, agent-based simulation, agent-based systems, model transformation, model-driven development, multi-agent systems, social models, social science, social simulation, social systems

In this paper, we present an automatic and efficient image based modelingsystem which can create objects' 3D models directly from images captured from different viewpoints. The system firstly uses structure from motion to generate camera parameters ... Keywords: automatic, image based modeling, patch, quasi dense, system

Management of regulated water systems has become increasingly complex due to rapid socio-economic growth and environmental changes in river basins over recent decades. This paper introduces the Source Integrated ModellingSystem (IMS), and describes ... Keywords: Murray-Darling Basin, Rainfall-runoff modelling, River management and operations, River systemmodelling, Source IMS

??This thesis presents the development of hybrid modeling methodologies for HVAC component static/steady-state models and dynamic/transient models, and the development and implementation of a model-based… (more)

In this paper models of Wind Parks (WPs) appropriate for simulation purposes of large power systems with high wind power penetration are developed. The proposed models of the WPs are developed using system identification theory with NARX model structures. ... Keywords: modeling, system identification, wind integration, wind parks, wind turbines

The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy ModelingSystem 2010, DOE/EIA-M068(2010). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

The classical tests of general relativity (perihelion precession, deflection of light, and the radar echo delay) are considered for the Dadhich, Maartens, Papadopoulos and Rezania (DMPR) solution of the spherically symmetric static vacuum field equations in brane world models. For this solution the metric in the vacuum exterior to a brane world star is similar to the Reissner-Nordstrom form of classical general relativity, with the role of the charge played by the tidal effects arising from projections of the fifth dimension. The existing observational solar system data on the perihelion shift of Mercury, on the light bending around the Sun (obtained using long-baseline radio interferometry), and ranging to Mars using the Viking lander, constrain the numerical values of the bulk tidal parameter and of the brane tension.

Model for Control and Automation Systems in Electrical Model for Control and Automation Systems in Electrical Power Reference Model for Control and Automation Systems in Electrical Power Modern infrastructure automation systems are threatened by cyber attack. Their higher visibility in recent years and the increasing use of modern information technology (IT) components contribute to increased security risk. A means of analyzing these infrastructure automation systems is needed to help understand and study the many system relationships that affect the overall security of the system. Modeling these systems is a very cost effective means of addressing the problem of security from an overall system view. The model presented in the document below provides a structured, cost effective approach to address technical security in process control systems

SEESM: Scalable Extensible Earth SystemModel for Climate Change Science SEESM: Scalable Extensible Earth SystemModel for Climate Change Science SEESM: Scalable Extensible Earth SystemModel for Climate Change Science This SciDAC project will transform an existing, state-of-the-science, third-generation global climate model, the Community Climate SystemModel (CCSM3), into a first-generation Earth systemmodel that fully simulates the relationships between the physical, chemical, and bio-geochemical processes in the climate system. The model will incorporate new processes necessary to predict future climates based on the specification of greenhouse gas emissions rather than specification of atmospheric concentrations, as is done in present models, which make assumptions about the carbon cycle that are likely not valid. This project will include comprehensive treatments of the processes

The Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy ModelingSystem is developed and maintained by the Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. This report documents the archived version of the NGTDM that was used to produce the natural gas forecasts presented in the Annual Energy Outlook 1996, (DOE/EIA-0383(96)). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic approach, and provides detail on the methodology employed. Previously this report represented Volume I of a two-volume set. Volume II reported on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.

This paper presents the development of a quasi-linear optimization model for a cogeneration system subject to constant heat and power demands or loads. The linear model is next modified to a non-linear one to account for economies of scale. The models define the necessary and sufficient conditions for system size optimality. Thus, the underlying methodology constitutes the foundation for a subsequent series of more sophisticated cogeneration design models. Several examples are presented to illustrate the models.

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Conceptual Models of Geothermal Systems - Introduction Conceptual Models of Geothermal Systems - Introduction Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Conceptual Models of Geothermal Systems - Introduction Abstract The key to the successful exploration, development (incl. drilling) and utilization of any type of geothermal system is a clear definition and understanding of the nature and characteristics of the system in question. This is best achieved through the development of a conceptual model of the system, which is a descriptive or qualitative model incorporating, and unifying, the essential physical features of the system. Conceptual models are mainly based on analysis of geological and geophysical information, temperature and pressure data, information on reservoir properties as well

Drainage systems can be categorized into natural or geomorphological drainage systems, agricultural drainage systems and urban drainage systems. They interact closely among themselves and with climate and human society, particularly under extreme climate and hydrological events such as floods. This editorial articulates the need to holistically understand and model drainage systems in the context of climate change and human influence, and discusses the requirements and examples of feasible approaches to representing natural and manmade drainage systems in an earth systemmodeling framework.

Workflows have proven to be a useful conceptualization for the automation of business processes. While formal verification methods (e.g., model checking) can help ensure the reliability of workflow systems, the industrial uptake of such methods has been ... Keywords: automated translation, distributed model checking, modeling, time, workflow systems

A thermal model was developed to estimate the energy losses from prototypical domestic hot water (DHW) distribution systems for homes. The developed model, using the TRNSYS simulation software, allows researchers and designers to better evaluate the performance of hot water distribution systems in homes. Modeling results were compared with past experimental study results and showed good agreement.

Hybrid Power System Simulation Model Hybrid Power System Simulation Model Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Hybrid Power System Simulation Model Focus Area: Renewable Energy Topics: System & Application Design Website: www.umass.edu/windenergy/OLD_SITE/projects/hybrid2/ Equivalent URI: cleanenergysolutions.org/content/hybrid-power-system-simulation-model, Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance This tool performs detailed long-term performance and economic analysis on a wide variety of hybrid power systems. It is a probabilistic/time-series computer model, using time-series data for loads, wind speed, solar insolation, temperature, and the power system designed or selected by the user, to predict the performance of the hybrid power system. An economic

A detailed component-based simulation model of a geothermal heat pump system has been calibrated to monitored data taken from a family housing unit located at Fort Polk, Louisiana. The simulation model represents the housing unit, geothermal heat pump, ground heat exchanger, thermostat, blower, and ground-loop pump. Each of these component models was 'tuned' to better match the measured data from the site. These tuned models were then interconnect to form the systemmodel. The systemmodel was then exercised in order to demonatrate its capabilities.

This document contains a description of the Advanced Simulation and Computing Program's Capability Computing System Governance Model. Objectives of the Governance Model are to ensure that the capability system resources are allocated on a priority-driven basis according to the Program requirements; and to utilize ASC Capability Systems for the large capability jobs for which they were designed and procured.

There are increasing numbers of systems and research projects involving software agents and mobile agents. However, there is no reference model or conceptual framework to compare the resulting systems. In this paper, we propose a reference model to identify, ... Keywords: agent-based applications, mobile agent systems, mobile agents

This document contains a description of the Advanced Simulation and Computing Program's Capability Computing System Governance Model. Objectives of the Governance Model are to ensure that the capability system resources are allocated on a priority-driven basis according to the Program requirements; and to utilize ASC Capability Systems for the large capability jobs for which they were designed and procured.

Abstract: We derive a dynamic systemmodel for biogeography-based optimization (BBO) that is asymptotically exact as the population size approaches infinity. The states of the dynamic system are equal to the proportion of each individual in the population; ... Keywords: Biogeography-based optimization, Dynamic system, Evolutionary algorithm, Genetic algorithm, Global uniform recombination, Markov model

In this paper, we present an approach to define the semantics for object-oriented modeling languages. One important property of this semantics is to support underspecified and incomplete models. To this end, semantics is given as predicates over elements ...

Four approaches to modeling multi-junction concentrating photovoltaic system performance are assessed by comparing modeled performance to measured performance. Measured weather, irradiance, and system performance data were collected on two systems over a one month period. Residual analysis is used to assess the models and to identify opportunities for model improvement. Large photovoltaic systems are typically developed as projects which supply electricity to a utility and are owned by independent power producers. Obtaining financing at favorable rates and attracting investors requires confidence in the projected energy yield from the plant. In this paper, various performance models for projecting annual energy yield from Concentrating Photovoltaic (CPV) systems are assessed by comparing measured system output to model predictions based on measured weather and irradiance data. The results are statistically analyzed to identify systematic error sources.

This report describes the RELAP5 model that has been developed for the divertor primary heat transfer system (PHTS). The model is intended to be used to examine the transient performance of the divertor PHTS and evaluate control schemes necessary to maintain parameters within acceptable limits during transients. Some preliminary results are presented to show the maturity of the model and examine general divertor PHTS transient behavior. The model can be used as a starting point for developing transient modeling capability, including control systemmodeling, safety evaluations, etc., and is not intended to represent the final divertor PHTS design. Preliminary calculations using the models indicate that during normal pulsed operation, present pressurizer controls may not be sufficient to keep system pressures within their desired range. Additional divertor PHTS and control system design efforts may be required to ensure system pressure fluctuation during normal operation remains within specified limits.

The purpose of this report is to define the objectives of the model, describe its basic approach, and provide detail on how it works. The EFP is a regulatory accounting model that projects electricity prices. The model first solves for revenue requirements by building up a rate base, calculating a return on rate base, and adding the allowed expenses. Average revenues (prices) are calculated based on assumptions regarding regulator lag and customer cost allocation methods. The model then solves for the internal cash flow and analyzes the need for external financing to meet necessary capital expenditures. Finally, the EFP builds up the financial statements. The EFP is used in conjunction with the National Energy ModelingSystem (NEMS). Inputs to the EFP include the forecast generating capacity expansion plans, operating costs, regulator environment, and financial data. The outputs include forecasts of income statements, balance sheets, revenue requirements, and electricity prices.

The Community Climate SystemModel version 3 (CCSM3) has recently been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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We present a data mining approach to model the cooling infrastructure in data centers, particularly the chiller ensemble. These infrastructures are poorly understood due to the lack of “first principles” models of chiller systems. At the ...

The use of diffusive terms in numerical ocean models is examined relative to different coordinate systems. The conventional model for horizontal diffusion is found to be incorrect when bottom topographical slopes are large. A new formulation is ...

The Inverse Ocean Modeling (IOM) system constructs and runs weak-constraint, four-dimensional variational data assimilation (W4DVAR) for any dynamical model and any observing array. The dynamics and the observing algorithms may be nonlinear but ...

The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top- down, modular principles ...

This report documents the various photovoltaic (PV) performance models and software developed and utilized by researchers at Sandia National Laboratories (SNL) in support of the Photovoltaics and Grid Integration Department. In addition to PV performance models, hybrid system and battery storage models are discussed. A hybrid system using other distributed sources and energy storage can help reduce the variability inherent in PV generation, and due to the complexity of combining multiple generation sources and system loads, these models are invaluable for system design and optimization. Energy storage plays an important role in reducing PV intermittency and battery storage models are used to understand the best configurations and technologies to store PV generated electricity. Other researcher's models used by SNL are discussed including some widely known models that incorporate algorithms developed at SNL. There are other models included in the discussion that are not used by or were not adopted from SNL research but may provide some benefit to researchers working on PV array performance, hybrid systemmodels and energy storage. The paper is organized into three sections to describe the different software models as applied to photovoltaic performance, hybrid systems, and battery storage. For each model, there is a description which includes where to find the model, whether it is currently maintained and any references that may be available. Modeling improvements underway at SNL include quantifying the uncertainty of individual system components, the overall uncertainty in modeled vs. measured results and modeling large PV systems. SNL is also conducting research into the overall reliability of PV systems.

Beliefs-Desires-Intentions models (or BDI models) of agents have been around for quit a long time. The purpose of these models is to characterize agents using anthropomorphic notions, such as mental states and actions. However, despite the fact that ...

. The results of the production cost model were compared to the 2007 historical operating conditions in the model. Â· Outages were simulated in MAPS based on 2007 historical outage duration by unit. In future analyses it is likely that the 5-year average outage data, by unit, would be implemented in the model

Geological Process Models (GPMs) have been used in the past to simulate the distinctive stratigraphies formed in carbonate sediments, and to explore the interaction of controls that produce heterogeneity. Previous GPMs have only indirectly included the ... Keywords: Carbonate, Geological process model, Numerical modeling, Reef, Supersaturation

Objects that are made up of multiple materials and known as heterogeneous objects are now increasingly being used in engineering applications. The development of new fabrication methods like rapid prototyping (RP), calls for new techniques to ... Keywords: CAD model, STL file, functionally graded material, geometric information, heterogeneous models, heterogeneous solids, layered manufacturing, manufacturing strategy, material information, rapid prototyping, solid modelling

This report provides a mathematical dynamical systemsmodel of the effect of plant processes and programs on nuclear plant safety. That is, it models the safety risk management process. Responses of this model to postulated changes in performance and coupling parameters were verified to be in accordance with experience from years of commercial nuclear power plant operation. A preliminary analysis of the model was performed using the techniques of dynamical systems theory to determine regions of operation...

We discuss solar system constraints on f(G) gravity models, where f is a function of the Gauss-Bonnet term G. We focus on cosmologically viable f(G) models that can be responsible for late-time cosmic acceleration. These models generally give rise to corrections of the form epsilon*(r/rs)^p to the vacuum Schwarzschild solution, where epsilon = H^2 rs^2 solar system constraints for a wide range of model parameters.

A computational and application-oriented introduction to the modeling of large-scale systems in a wide variety of decision-making domains and the optimization of such systems using state-of-the-art optimization software. ...

Report on System Simulation using High Performance Computing Prepared by New Mexico Tech New Mexico: Application of High Performance Computing to Electric Power SystemModeling, Simulation and Analysis Task Two

The Regional Ocean ModelingSystem (ROMS) is used to systematically investigate equilibrium conditions and seasonal variations of the Benguela system at a resolution of 9 km, including both the large-scale offshore flow regime and the ...

The presented work is a compilation of four different projects related to axial and centrifugal compression systems. The projects are related by the underlying dynamic systemmodeling approach that is common in all of them. ...

The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was organized to promote the development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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The fourth version of the Community Climate SystemModel (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than the CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.

Reproducibility is a pillar of the scientific endeavour. We view computer simulations as laboratories for electronic experimentation and therefore as tools for science. Recent studies have addressed model reproduction and found it to be surprisingly difficult to replicate published findings. There have been enough failed simulation replications to raise the question, 'can computer models be fully replicated?' This paper answers in the affirmative by reporting on a successful reproduction study using Mathematica, Repast and Swarm for the Beer Game supply chain model. The reproduction process was valuable because it demonstrated the original result's robustness across modelling methodologies and implementation environments.

for Evaluation of System Level Modeling for Evaluation of System Level Modeling and Simulation Tools in Support of Hanford Site Liquid Waste Process External Technical Review for Evaluation of System Level Modeling and Simulation Tools in Support of Hanford Site Liquid Waste Process Full Document and Summary Versions are available for download External Technical Review for Evaluation of System Level Modeling and Simulation Tools in Support of Hanford Site Liquid Waste Process Summary - System Level Modeling and Simulation Tools for Hanford More Documents & Publications Hanford Site C Tank Farm Meeting Summary - May 2009 System Planning for Low-Activity Waste at Hanford Hanford ETR Tank Waste Treatment and Immobilization Plant - Hanford Tank Waste Treatment and Immobilization Plant Technical Review - External

Numerical Modeling Of Basin And Range Geothermal Systems Numerical Modeling Of Basin And Range Geothermal Systems Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: Numerical Modeling Of Basin And Range Geothermal Systems Details Activities (3) Areas (3) Regions (0) Abstract: Basic qualitative relationships for extensional geothermal systems that include structure, heat input, and permeability distribution have been established using numerical models. Extensional geothermal systems, as described in this paper, rely on deep circulation of groundwater rather than on cooling igneous bodies for heat, and rely on extensional fracture systems to provide permeable upflow paths. A series of steady-state, two-dimensional simulation models is used to evaluate the effect of permeability and structural variations on an idealized, generic

This chapter presents what a future environment for building systemmodeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described by coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).

This chapter presents what a future environment for building systemmodeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described by coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).

The National Renewable Energy Laboratory (NREL) has developed a transient air conditioning (A/C) systemmodel using SINDA/FLUINT analysis software. It captures all the relevant physics of transient A/C system performance, including two-phase flow effects in the evaporator and condenser, system mass effects, air side heat transfer on the condenser/evaporator, vehicle speed effects, temperature-dependent properties, and integration with a simplified cabin thermal model. It has demonstrated robust and powerful system design optimization capabilities. Single-variable and multiple variable design optimizations have been performed and are presented. Various system performance parameters can be optimized, including system COP, cabin cool-down time, and system heat load capacity. This work presents this new transient A/C system analysis and optimization tool and shows some high-level system design conclusions reached to date. The work focuses on R-134a A/C systems, but future efforts will modify the model to investigate the transient performance of alternative refrigerant systems such as carbon dioxide systems. NREL is integrating its transient air conditioning model into NRELs ADVISOR vehicle system analysis software, with the objective of simultaneously optimizing A/C system designs within the overall vehicle design optimization.

This paper presents a modified current-voltage relationship for the single diode model. The single-diode model has been derived from the well-known equivalent circuit for a single photovoltaic cell. The modification presented in this paper accounts for both parallel and series connections in an array.

Work system analysis and design is complex and nondeterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human-machine systems. Brahms was originally conceived as a business ... Keywords: Agent Languages, Business Process Modeling, Mission Operations Design, Multiagent Simulation, Work Practices

Given the great emphasis being placed on energy efficiency in contemporary society, in which the smart grid plays a prominent role, this is an opportune time to explore methodologies for appropriately representing system attributes. We suggest this is ... Keywords: Smart grid, System representativeness

As a model of decohering environment, we show that quantum chaotic system behave equivalently as many-body system. An approximate formula for the time evolution of the reduced density matrix of a system interacting with a quantum chaotic environment is derived. This theoretical formulation is substantiated by the numerical study of decoherence of two qubits interacting with a quantum chaotic environment modeled by a chaotic kicked top. Like the many-body model of environment, the quantum chaotic system is efficient decoherer, and it can generate entanglement between the two qubits which have no direct interaction.

Propulsion systems based on the polymer electrolyte fuel cell (PEFC) are being developed. This paper reports an analysis undertaken to design improved PEFC systems. A reference system design with some variants were set up for a methanol-fueled PEFC propulsion system. Efficiency improves from 38.4 to 44.1% as cell current density goes from 0.75 to 0.45 A/cm{sup 2}, while fuel cell efficiency increases from 52.6 to 60.0%; to get a net power output of 80 kWe, the active fuel cell area must increase from 18.8 to 27.3 m{sup 2}. Three parametric studies were conducted on the off-design performance of the reference system.

Economic and Power SystemModeling and Analysis Economic and Power SystemModeling and Analysis NREL's Economic Analysis and power systemmodeling integrates data from device deployment and programmatic research into deployment and scenario models to quantify the economic and societal benefits of developing cost-competitive marine and hydrokinetic systems. It also identifies policy mechanisms, market designs, and supply chain needs to support various deployment scenarios, provide information and training to potential members of the marine and hydrokinetic (MHK) industry and effectively collaborate with all associated stakeholders. JEDI Modeling NREL worked with industry members to develop and provide public access to an easy-to-use input-output model that estimates the jobs and economic development impacts (JEDI) of MHK projects in the United States. The JEDI

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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they are not comprehensive nor are they the most current set.
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In this chapter we show the ability to specify with SystemC under the restrictions imposed by several model of computations, namely CSP, KPN and SR. Specifying under these MoCs provides some important properties, specially deterrninism and more protection ... Keywords: CSP, KPN, SR, model of computation, system-level design, systemC

We have carried out detailed simulations of various fields in the USA (Bada, New Mexico; Heber, California); Mexico (Cerro Prieto); Iceland (Krafla); and Kenya (Olkaria). These simulation studies have illustrated the usefulness of numerical models for the overall evaluation of geothermal systems. The methodology for modeling the behavior of geothermal systems, different approaches to geothermal reservoir modeling and how they can be applied in comprehensive evaluation work are discussed.

This paper explores the role of user modelling in live help systems for e-commerce web sites. There are several potential benefits with user modelling in this context: 1) Human assistants can use the personal information in the user models to provide ...

Most volume modellingsystems are very limited in the complexity of the surfaces which they support. This is satisfactory for basic models of most mechanical components, since the functional surfaces are not usually complex. However, there are often ... Keywords: computer aided design, curved surfaces, ray tracing, volume modelling

Shades in buildings are widely installed and are an effective technique for managing solar gains and occupant comfort. A model of a typical office space located in Ottawa, Ontario has been created and the model was developed for analysis under variable ... Keywords: energy management system, model predictive control, reactive control, shades

Electrocatalytic reaction systems demonstrate markedly different behavior than those carried out in the vapor phase or under ultrahigh vacuum conditions. The differences in reactivity can be attributed to the significant difference between the reaction environment o fht electrocatalytic system which includes the presence of solution, electrolyte, and intrinsic as well as extrinsic potentials, in addition to the vapor phase system. The solution environment and the applied potential can stabilize or destabilize charge transfer events, thus influencing many of the physiochemical processes that occur at the surface of a working electrode and strongly impacting the activity, as well as the selectivity of the active catalyst.

The performance of a wireless system depends on the wireless channel as well as the algorithms used in the transceiver pipelines. Because physical phenomena affect transceiver pipelines in difficult to predict ways, detailed ...

Future end systems, so-called 'workstations', will consist of a variety of different, sometimes intergrated devices. These devices may vary from character-oriented display terminals to database-oriented storage devices. The aim of the presentation service ...

This paper presents the evolution of control systems and trends in the field of integrated computer, communication and cognitive sciences for control applications. There have been selected and presented the most efficient control strategies used in complex ... Keywords: intelligent control systems, model-based systems

The evolution of electric power system analysis methods followed the present technical problems and business needs of electric utilities in Romania, before EU integration. Present technical requirements and the current stage of power system analysis ... Keywords: Fourier analysis, computer applications, computer simulation, modelling, power systems, training

The evolution of electric power system analysis methods followed the present technical problems and business needs of electric utilities in Romania, before EU integration. Present technical requirements and the current stage of power system analysis ... Keywords: computer applications, computer simulation, fourier analysis, modelling, power systems, training

Viewing an urban water system as a complex adaptive system provides new opportunities for analysis and avoids some critical simplifications. Taking this perspective, it is possible to explore the inter-related effects of changes to the system. This is ... Keywords: Agent-based modelling, Integrated assessment, Socio-technical analysis, Water services

Detailed models for hydrogen storage systems provide essential design information about flow and temperature distributions, as well as, the utilization of a hydrogen storage media. However, before constructing a detailed model it is necessary to know the geometry and length scales of the system, along with its heat transfer requirements, which depend on the limiting reaction kinetics. More fundamentally, before committing significant time and resources to the development of a detailed model, it is necessary to know whether a conceptual storage system design is viable. For this reason, a hierarchical system of models progressing from scoping models to detailed analyses was developed. This paper, which discusses the scoping models, is the first in a two part series that presents a collection of hierarchical models for the design and evaluation of hydrogen storage systems.

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

The air–land–sea interaction in the vicinity of Monterey Bay, California, is simulated and investigated using a new Integrated Regional ModelSystem (I-RMS). This new model realistically resolves coastal processes and submesoscale features that ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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The objective of this research is to investigate incorporating a wetland component into a land energy and water fluxes model, the Community Land Model (CLM). CLM is the land fluxes component of the Integrated Global Systems ...

Both historical and idealized climate model experiments are performed with a variety of Earth systemmodels of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate ...

The Community Surface Dynamics ModelingSystem (CSDMS) is a community of earth scientists promoting the modeling of earth surface processes by developing and disseminating integrated software modules that predict the movement of fluids, and the flux ... Keywords: Community modeling, Earth surface dynamics, Governance, Model integration

The Community Earth SystemModel (CESM) is a flexible and extensible community tool used to investigate a diverse set of earth system interactions across multiple time and space scales. This global coupled model is a natural evolution from its predecessor, the Community Climate SystemModel, following the incorporation of new earth system capabilities. These include the ability to simulate biogeochemical cycles, atmospheric chemistry, ice sheets, and a high-top atmosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new predictive capabilities and increasing our collective knowledge about the behavior and interactions of the earth system. Simulations with numerous configurations of the CESM have been provided to the Coupled Model Intercomparison Project Phase 5 (CMIP5) and are being analyzed by the broader community of scientists. Additionally, the model source code and associated documentation are freely available to the scientific community to use for earth system studies, making it a true community tool. Here we describe this earth modelingsystem, its various possible configurations, and illustrate its capabilities with a few science highlights.

CARBON EMISSIONS CARBON EMISSIONS A part of the integrating module, the carbon emissions submodule (CEM) computes the carbon emissions due to the combustion of energy. The coefficients for carbon emissions are derived from Energy Information Administration, Emissions of Greenhouse Gases in the United States 1996, published in October 1997. The calculations account for the fact that some fossil fuels are used for nonfuel purposes, such as feedstocks, and thus the carbon in the fuel is sequestered in the end product. CEM also allows for several carbon policy evaluation options to be imposed within NEMS. Although none of the policy options are assumed in the Annual Energy Outlook 1998, the options can be used in special analyses to simulate potential market-based approaches to meet national carbon emission

technology vehicles (i.e., diesel, hybrid, and fuel cell) developed for improved fuel economy remains either be done through Argonne National laboratory's hybrid vehicle cost model algorithm (adapted the Tool Can Help Answer Â· What is the life cycle cost of today's midsize hybrid vehicle? Â· How does

Most of other technologically important systems (among them, powders and other granular systems) are intrinsically nonlinear. This project is focused on building the dynamical models for granular systems as a prototype for nonlinear high-dimensional systems exhibiting complex non-equilibrium phenomena. Granular materials present a unique opportunity to study these issues in a technologically important and yet fundamentally interesting setting. Granular systems exhibit a rich variety of regimes from gas-like to solid-like depending on the external excitation. Based the combination of the rigorous asymptotic analysis, available experimental data and nonlinear signal processing tools, we developed a multi-scale approach to the modeling of granular systems from detailed description of grain-grain interaction on a micro-scale to continuous modeling of large-scale granular flows with important geophysical applications.

Using Modelica for Physical Modeling of Air-Conditioning Systems Using Modelica for Physical Modeling of Air-Conditioning Systems Speaker(s): Jonas Eborn Date: August 23, 2007 - 12:00pm Location: 90-4133 Seminar Host/Point of Contact: Michael Wetter The Air Conditioning library is a commercial Modelica library for the steady-state and transient simulation of air conditioning systems using both compact micro-channel heat exchangers as well as fin-and-tube type heat exchangers. Currently it is mostly used by automotive OEMs and suppliers that need high-accuracy system level models to evaluate energy efficiency of systems developed under the pressure of reduced design cycle times. The library also has applications in other areas, including aircraft cooling systems and residential air-conditioning. The Air Conditioning library contains published correlations for heat and mass transfer and

Several techniques for specification exist to capture certain aspects of user behaviour, with the goal of reasoning about the usability of the system and other human-factors related issues. One such approach is to encode a set of assumptions about user ...

This presentation describes some the data requirements needed for grid integration modeling and provides real-world examples of such data and its format. Renewable energy integration studies evaluate the operational impacts of variable generation. Transmission planning studies investigate where new transmission is needed to transfer energy from generation sources to load centers. Both use time-synchronized wind and solar energy production and load as inputs. Both examine high renewable energy penetration scenarios in the future.

The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.

Simulation studies for large infrastructure systems often consists of a large number of experiments. Performing all experiments, and the required adjustments to simulation models, is time consuming. In addition it is difficult to keep track of all performed ...

Abstract from Technical Report Documentation Page: This report is intended to serve as a guide to the availability and capability of state-of-the-art analytical and simulation models of the National Airspace System (NAS). ...

There is a greater need than ever for the ability to accurately model urban system impacts resulting around the planet. Rapid urbanization is transforming landscapes from vegetation to an engineered infrastructure and thus altering land cover and ...

Strong multidecadal variability is detected in a 300-yr integration of the NCAR Climate SystemModel in the South Atlantic region, through the application of two signal recognition techniques: the multitaper method and singular spectrum analysis. ...

The Second Workshop on Coupling Technologies for Earth SystemModels (CW2013) was recently held at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. The goals of the workshop were to update participants on recent developments in ...

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
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Over the past year, several modifications have been made to the NEMS Transportation Model,incorporating greater levels of detail and analysis in modules previously represented in the aggregate or under a profusion of simplifying assumptions. This document is intended to amend those sections of the Model Documentation Report (MDR) which describe these superseded modules.

Compact, on-site fuel reprocessing and waste management for the Integral Fast Reactor are based on the pyrochemical reprocessing of metal fuel. In that process, uranium and plutonium in spent fuel are separated from fission products in an electrorefiner using liquid cadmium and molten salt solvents. Quantitative estimates of the distribution of the chemical elements among the metal and salt phases are essential for development of both individual pyrochemical process steps and the complete process. This paper describes the PYRO system of programs used to generate reliable mass flows and compositions.

Nuclear Systems Nuclear SystemsModeling and Design Analysis CAPABILITIES Overview Nuclear SystemsModeling and Design Analysis Nuclear Systems Technologies Risk and Safety Assessments Nonproliferation and National Security Materials Testing Engineering Computation & Design Engineering Experimentation Work with Argonne Contact us For Employees Site Map Help Join us on Facebook Follow us on Twitter NE on Flickr Celebrating the 70th Anniversary of Chicago Pile 1 (CP-1) Argonne OutLoud on Nuclear Energy Argonne Energy Showcase 2012 Capabilities Nuclear SystemsModeling and Design Analysis Bookmark and Share Reactor Physics and Fuel Cycle Analysis Reactor Physics and Fuel Cycle Analysis We have played a major role in the design and analysis of most existing and past reactor types and of many

This paper presents a coupled modeling framework to capture the dynamic linkages between agricultural and energy markets that have been enhanced through the expansion of biofuel production, as well as the environmental impacts resulting from this expansion. ... Keywords: Agricultural markets, Biofuels, Energy systems, Environment, Modeling

We suggest a simple synthesis model of an eclipsing binary system which includes one component with strong stellar wind. Numerical simulations show that the shape of the light curve (and in particularly the widths of the minima) strongly depends on wind parameters. Wind effects are crucial in modelling light curves of binaries including e.g., WR stars.

In this paper we present a modelling and visualization design approach for context-aware systems, specifically focusing on applications that support location tracking and that exhibit their behaviour as actuations in the deployment environment. The design ... Keywords: Context awareness, design tool, modelling, prototyping, simulation, test-bed, ubiquitous computing

Root cause localization, the process of identifying the source of problems in a system using purely external observations, is a significant challenge in many large-scale systems. In this paper, we propose an abstract model that captures the common issues ...

an end-to-end storage systemmodel of the Argonne Leadership Computing Facility's (ALCF) comput- ing collected from the ALCF's storage system for a variety of synthetic I/O workloads and scales. we present in the ALCF. As an early study of the CODES project, our simulators can quickly and accurately simulate

In this article we present an approach to the design of human-like artificial systems. It uses a perception model to describe how sensory information is processed for a particular task and to correlate human and artificial perception. Since human-like ... Keywords: Active perception, Artificial hand, Artificial perceptual systems, Dexterous manipulation, Electronic tongue, Human-based sensors, Passive perception

BIP is a component-based framework supporting rigorous design of embedded systems. This paper presents SBIP, an extension of BIP that relies on a new stochastic semantics that enables verification of large-size systems by using Statistical Model Checking. ...

We present a visual feedback method for closed loop control of automated microassembly. A CAD model based multi-camera visual tracking system that is well suited for flexible automation and assembly of complex 3D geometries was developed. The system ... Keywords: CAD, Microassembly, Micromanipulation, Visual servoing, Visual tracking

PV performance models are used to predict how much energy a PV system will produce at a given location and subject to prescribed weather conditions. These models are commonly used by project developers to choose between module technologies and array designs (e.g., fixed tilt vs. tracking) for a given site or to choose between different geographic locations, and are used by the financial community to establish project viability. Available models can differ significantly in their underlying mathematical formulations and assumptions and in the options available to the analyst for setting up a simulation. Some models lack complete documentation and transparency, which can result in confusion on how to properly set up, run, and document a simulation. Furthermore, the quality and associated uncertainty of the available data upon which these models rely (e.g., irradiance, module parameters, etc.) is often quite variable and frequently undefined. For these reasons, many project developers and other industry users of these simulation tools have expressed concerns related to the confidence they place in PV performance model results. To address this problem, we propose a standardized method for the validation of PV system-level performance models and a set of guidelines for setting up these models and reporting results. This paper describes the basic elements for a standardized model validation process adapted especially for PV performance models, suggests a framework to implement the process, and presents an example of its application to a number of available PV performance models.

We describe how to develop a suite of models in the MS4 Modeling Environment. The approach employs the operation of merging of System Entity Structures supported by the environment. After construction, the suite of models can be hosted on Model Store, ... Keywords: component-based modeling, suite of models, system entity structure, systems of systems

Beijing is a typical North China city, and it uses about 15-18% of its total energy consumption for heating. The building construction industry is also a key source of CO2 emissions. This article, based on a system dynamics model, aims to simulate and ... Keywords: CO2 emissions, energy consumption, heating system, system dynamics

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
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The Texas Water Resources Institute (TWRI), and many other agencies and organizations, have worked with Ralph Wurbs over the years to develop WRAP (the Water Rights Analysis Package). The WRAP model simulates management of the water resources of a river basin, or multiple-basin region, under a priority-based water allocation system. The model facilitates assessment of hydrologic and institutional water availability/reliability for existing and proposed requirements for water use and management. Basin-wide impacts of water resources development projects and management strategies may be evaluated. The software package is generalized for application to any river/reservoir/use system, with input files being developed for the particular river basin of concern. The model is documented by reference and users manuals that may be downloaded from this site along with the software. WRAP is incorporated in the Texas Commission on Environmental Quality (TCEQ) Water Availability Modeling (WAM) System.

Geothermometers And Mixing Models For Geothermal Systems Geothermometers And Mixing Models For Geothermal Systems Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: Chemical Geothermometers And Mixing Models For Geothermal Systems Details Activities (1) Areas (1) Regions (0) Abstract: Qualitative chemical geothermometers utilize anomalous concentrations of various "indicator" elements in groundwaters, streams, soils, and soil gases to outline favorable places to explore for geothermal energy. Some of the qualitative methods, such as the delineation of mercury and helium anomalies in soil gases, do not require the presence of hot springs or fumaroles. However, these techniques may also outline fossil thermal areas that are now cold. Quantitative chemical geothermometers and mixing models can provide information about present probable minimum

The purpose of this whitepaper is to provide a framework for understanding the role that Verification and Validation (V&V), Uncertainty Quantification (UQ) and Risk Quantification, collectively referred to as VU, is expected to play in modeling nuclear energy systems. We first provide background for the modeling of nuclear energy based systems. We then provide a brief discussion that emphasizes the critical elements of V&V as applied to nuclear energy systems but is general enough to cover a broad spectrum of scientific and engineering disciplines that include but are not limited to astrophysics, chemistry, physics, geology, hydrology, chemical engineering, mechanical engineering, civil engineering, electrical engineering, nu nuclear engineering material clear science science, etc. Finally, we discuss the critical issues and challenges that must be faced in the development of a viable and sustainable VU program in support of modeling nuclear energy systems.

Surficial Extent And Conceptual Model Of Hydrothermal System At Mount Surficial Extent And Conceptual Model Of Hydrothermal System At Mount Rainier, Washington Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: Surficial Extent And Conceptual Model Of Hydrothermal System At Mount Rainier, Washington Details Activities (4) Areas (2) Regions (0) Abstract: A once massive hydrothermal system was disgorged from the summit of Mount Rainier in a highly destructive manner about 5000 years ago. Today, hydrothermal processes are depositing clayey alteration products that have the potential to reset the stage for similar events in the future. Areas of active hydrothermal alteration occur in three representative settings: 1. (1) An extensive area (greater than 12,000 m2) of heated ground and slightly acidic boiling-point fumaroles at 76-82Â°C at

There is significant interest in hydrogen storage systems that employ a media which either adsorbs, absorbs or reacts with hydrogen in a nearly reversible manner. In any media based storage system the rate of hydrogen uptake and the system capacity is governed by a number of complex, coupled physical processes. To design and evaluate such storage systems, a comprehensive methodology was developed, consisting of a hierarchical sequence of models that range from scoping calculations to numerical models that couple reaction kinetics with heat and mass transfer for both the hydrogen charging and discharging phases. The scoping models were presented in Part I [1] of this two part series of papers. This paper describes a detailed numerical model that integrates the phenomena occurring when hydrogen is charged and discharged. A specific application of the methodology is made to a system using NaAlH{sub 4} as the storage media.

Research barriers continue to exist in all phases of the emerging cellulosic ethanol biorefining industry. These barriers include the identification and development of a sustainable and abundant biomass feedstock, the assembly of viable assembly systems formatting the feedstock and moving it from the field (e.g., the forest) to the biorefinery, and improving conversion technologies. Each of these phases of cellulosic ethanol production are fundamentally connected, but computational tools used to support and inform analysis within each phase remain largely disparate. This paper discusses the integration of a feedstock assembly systemmodeling toolkit and an Aspen Plus® conversion process model. Many important biomass feedstock characteristics, such as composition, moisture, particle size and distribution, ash content, etc. are impacted and most effectively managed within the assembly system, but generally come at an economic cost. This integration of the assembly system and the conversion process modeling tools will facilitate a seamless investigation of the assembly system conversion process interface. Through the integrated framework, the user can design the assembly system for a particular biorefinery by specifying location, feedstock, equipment, and unit operation specifications. The assembly systemmodeling toolkit then provides economic valuation, and detailed biomass feedstock composition and formatting information. This data is seamlessly and dynamically used to run the Aspen Plus® conversion process model. The model can then be used to investigate the design of systems for cellulosic ethanol production from field to final product.

Modeling and Simulation of a Solar Assisted Desiccant Cooling SystemModeling and Simulation of a Solar Assisted Desiccant Cooling System Speaker(s): Chadi Maalouf Date: December 2, 2004 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Peng Xu Increased living standards and high occupants comfort demands lead to a growth in air conditioning market. This results in high energy consumption and high CO2 emissions. For these reasons, the solar desiccant cooling system is proposed as an alternative to traditional air conditioning systems. This system comprises a desiccant wheel containing Lithium Chloride in tandem with a rotating heat exchanger and two humidifiers on both supply and return air. The required regeneration temperature for the desiccant wheel varies between 40oC and 70oC which makes possible the use

energy modeling programs comparison Research on HVAC systems energy modeling programs comparison Research on HVAC systems simulation part Title Building energy modeling programs comparison Research on HVAC systems simulation part Publication Type Journal Year of Publication 2013 Authors Zhou, Xin, Da Yan, Tianzhen Hong, and Dandan Zhu Keywords Building energy modeling programs, comparison tests, HVAC system simulation, theory analysis Abstract Building energy simulation programs are effective tools for the evaluation of building energy saving and optimization of design. The fact that large discrepancies exist in simulated results when different BEMPs are used to model the same building has caused wide concern. Urgent research is needed to identify the main elements that contribute towards the simulation results. This technical report summarizes methodologies, processes, and the main assumptions of three building energy modeling programs (BEMPs) for HVAC calculations: EnergyPlus, DeST, and DOE-2.1E, and test cases are designed to analyze the calculation process in detail. This will help users to get a better understanding of BEMPs and the research methodology of building simulation. This will also help build a foundation for building energy code development and energy labeling programs.

System energy models are important for energy optimization and management in mobile systems. However, existing system energy models are built in a lab setting with the help from a second computer. Not only are they labor-intensive; but also they do not adequately account for the great diversity in the hardware and usage of mobile systems. Moreover, existing system energy models are intended for energy estimation for time intervals of one second or longer; they do not provide the required rate for fine-grain use such as per-application energy accounting. In this work, we study a self-modeling paradigm in which a mobile system automatically generates its energy model without any external assistance. Our solution, Sesame, leverages the possibility of self power measurement through the smart battery interface and employs a suite of novel techniques to achieve accuracy and rate much higher than that of the smart battery interface. We report the implementation and evaluation of Sesame on a laptop and a smartphone. The experiment results show that Sesame is able to generate system energy models of 95 % accuracy at one estimation per second and of 88 % accuracy at one estimation per 10 ms, without any external assistance. Two fiveday field studies with four laptop and four smartphones users further demonstrate the effectiveness, efficiency, and noninvasiveness of Sesame.

A numerical simulator was developed for the modeling of air-steam-water systems. The simulator was applied to various problems involving injection into or production from a geothermal reservoir in hydraulic communication with a shallow free-surface aquifer. First, a one-dimensional column problem is considered and the water level movement during exploitation is studied using different capillary pressure functions. Second, a two-dimensional radial model is used to study and compare reservoir depletion for cases with and without a free-surface aquifer. Finally, the contamination of a shallow free-surface aquifer due to cold water injection is investigated. The primary aim of these studies is to obtain an understanding of the response of a reservoir in hydraulic communication with a unconfined aquifer during exploitation or injection and to determine under which circumstances conventional modeling techniques (fully saturated systems) can be applied to such systems.

There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids (including wind turbines, PV, diesel generators, AC/DC energy storage) as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, NREL and U. Mass. researchers developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed.

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon Â» A Geochemical Model Of The Platanares Geothermal System, Honduras Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: A Geochemical Model Of The Platanares Geothermal System, Honduras Details Activities (0) Areas (0) Regions (0) Abstract: Results of exploration drilling combined with results of geologic, geophysical, and hydrogeochemical investigations have been used to construct a geochemical model of the Platanares geothermal system, Honduras. Three coreholes were drilled, two of which produced fluids from fractured Miocene andesite and altered Cretaceous to Eocene conglomerate at

System Advisor Model, System Advisor Model, SAM 2011.12.2: General Description Paul Gilman and Aron Dobos Technical Report NREL/TP-6A20-53437 February 2012 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 System Advisor Model, SAM 2011.12.2: General Description Paul Gilman and Aron Dobos Prepared under Task No. SS12.1130 Technical Report NREL/TP-6A20-53437 February 2012 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government.

Gaussian Process Modeling: Applications to Building Systems and Algorithmic Gaussian Process Modeling: Applications to Building Systems and Algorithmic Challenges Speaker(s): Victor M. Zavala Date: November 5, 2013 - 12:00pm - 1:00pm Location: 90-3122 Seminar Host/Point of Contact: Mary Ann Piette Michael Sohn We review applications and algorithmic challenges of Gaussian Process (GP) modeling. GP is a powerful and flexible uncertainty quantification and data analysis technique that enables the construction of complex models without the need to specify algebraic relationships between variables. This is done by working directly in the space of the kernel or covariance matrix. In addition, it derives from a Bayesian framework and, as such, it naturally provides predictive probability distributions. We describe how these features can be exploited in Measurement and Verification (M&V) tasks and

The MIT Integrated Global SystemModel (IGSM) is designed for analyzing the global environmental changes that may result from anthropogenic causes, quantifying the uncertainties associated with the projected changes, and ...

Structural dynamic systems are often attached to a support structure to simulate proper boundary conditions during testing. In some cases the support structure is fairly simple and can be modeled by discrete springs and dampers. In other cases the desired test conditions necessitate the use of a support structural that introduces dynamics of its own. For such cases a more complex structural dynamic model is required to simulate the response of the full combined system. In this paper experimental frequency response functions, admittance function modeling concepts, and least squares reductions are used to develop a support structure model including both translational and rotational degrees of freedom at an attachment location. Subsequently, the modes of the support structure are estimated, and a NASTRAN model is created for attachment to the tested system.

This user guide describes the macro systemmodel (MSM). The MSM has been designed to allow users to analyze the financial, environmental, transitional, geographical, and R&D issues associated with the transition to a hydrogen economy. Basic end users can use the MSM to answer cross-cutting questions that were previously difficult to answer in a consistent and timely manner due to various assumptions and methodologies among different models.

One way to reduce the effects of anthropogenic greenhousegases on climate is to inject carbon dioxide (CO2) from industrialsources into deep geological formations such as brine formations ordepleted oil or gas reservoirs. Research has and is being conducted toimprove understanding of factors affecting particular aspects ofgeological CO2 storage, such as performance, capacity, and health, safetyand environmental (HSE) issues, as well as to lower the cost of CO2capture and related processes. However, there has been less emphasis todate on system-level analyses of geological CO2 storage that considergeological, economic, and environmental issues by linking detailedrepresentations of engineering components and associated economic models.The objective of this study is to develop a system-level model forgeological CO2 storage, including CO2 capture and separation,compression, pipeline transportation to the storage site, and CO2injection. Within our systemmodel we are incorporating detailedreservoir simulations of CO2 injection and potential leakage withassociated HSE effects. The platform of the system-level modelingisGoldSim [GoldSim, 2006]. The application of the systemmodel is focusedon evaluating the feasibility of carbon sequestration with enhanced gasrecovery (CSEGR) in the Rio Vista region of California. The reservoirsimulations are performed using a special module of the TOUGH2 simulator,EOS7C, for multicomponent gas mixtures of methane and CO2 or methane andnitrogen. Using this approach, the economic benefits of enhanced gasrecovery can be directly weighed against the costs, risks, and benefitsof CO2 injection.

international energy module (IEM) consists of four submodules (Figure 4) that perform the following functions: international energy module (IEM) consists of four submodules (Figure 4) that perform the following functions: world oil market submoduleÂ—calculates the average annual world oil price (imported refiner acquisition cost) that is consistent with worldwide petroleum demand and supply availability crude oil supply submoduleÂ—provides im- ported crude oil supply curves for five crude oil quality classes petroleum products supply submoduleÂ—pro- vides imported refined product supply curves for eleven types of refined products oxygenates supply submoduleÂ—provides imported oxygenates supply curves for methyl tertiary butyl ether (MTBE) and methanol. Figure 4. International Energy Module Structure The world oil price that is generated by the world oil market submodule is used by all the modules of NEMS as well as the other submodules of IEM. The import supply curves for crude oils, refined products, and oxygenates are used by the petroleum market module.

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

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A part of the integrating module, the carbon emissions submodule (CEM), computes the carbon emissions from the combustion of energy. The coefficients for carbon emissions are derived from Energy Information Administration, Emissions of Greenhouse Gases in the United States 1998,14 published in October 1999. The coefficients account for the fact that some fossil fuels are used for nonfuel purposes, such as feedstocks, and thus the carbon in the fuel is sequestered in the end product. A part of the integrating module, the carbon emissions submodule (CEM), computes the carbon emissions from the combustion of energy. The coefficients for carbon emissions are derived from Energy Information Administration, Emissions of Greenhouse Gases in the United States 1998,14 published in October 1999. The coefficients account for the fact that some fossil fuels are used for nonfuel purposes, such as feedstocks, and thus the carbon in the fuel is sequestered in the end product. CEM also allows for several carbon policy evaluation options to be analyzed within NEMS. Although these policy options are not assumed in the Annual Energy Outlook 2000, the options have been used in special analyses to simulate potential market-based approaches to meet national carbon emission objectives. The policy options implemented in CEM are as follows:

This paper presents the technical formulation and demonstrated model performance results of a new direct-steam-generation (DSG) model in NREL's System Advisor Model (SAM). The model predicts the annual electricity production of a wide range of system configurations within the DSG Linear Fresnel technology by modeling hourly performance of the plant in detail. The quasi-steady-state formulation allows users to investigate energy and mass flows, operating temperatures, and pressure drops for geometries and solar field configurations of interest. The model includes tools for heat loss calculation using either empirical polynomial heat loss curves as a function of steam temperature, ambient temperature, and wind velocity, or a detailed evacuated tube receiver heat loss model. Thermal losses are evaluated using a computationally efficient nodal approach, where the solar field and headers are discretized into multiple nodes where heat losses, thermal inertia, steam conditions (including pressure, temperature, enthalpy, etc.) are individually evaluated during each time step of the simulation. This paper discusses the mathematical formulation for the solar field model and describes how the solar field is integrated with the other subsystem models, including the power cycle and optional auxiliary fossil system. Model results are also presented to demonstrate plant behavior in the various operating modes.

This paper discusses further developments and refinements for the uses of the Geothermal System Scoping Model in an effort to provide a means for performing a variety of trade-off analyses of surface and subsurface parameters, sensitivity analyses, and other systems engineering studies in order to better inform R&D direction and investment for the development of geothermal power into a major contributor to the U.S. energy supply.

In this study, an interactive decision support system (UREM-IDSS) has been developed based on an inexact optimization model (UREM, University of Regina Energy Model) to aid decision makers in planning energy management systems. Optimization modeling, ... Keywords: Decision making, Energy management systems, Green house gas, Interactive decision support system, Optimization, Sustainable development, Uncertainty

To improve the system performance of the GHP, modeling and experimental study has been made by using desiccant system in cooling operation (particularly in high humidity operations) and suction line waste heat recovery to augment heating capacity and efficiency. The performance of overall GHP system has been simulated by using ORNL Modulating Heat Pump Design Software, which is used to predict steady-state heating and cooling performance of variable-speed vapor compression air-to-air heat pumps for a wide range of operational variables. The modeling includes: (1) GHP cycle without any performance improvements (suction liquid heat exchange and heat recovery) as a baseline (both in cooling and heating mode), (2) the GHP cycle in cooling mode with desiccant system regenerated by waste heat from engine incorporated, (3) GHP cycle in heating mode with heat recovery (recovered heat from engine). According to the systemmodeling results, by using desiccant system regenerated by waste heat from engine, the SHR can be lowered to 40%. The waste heat of the gas engine can boost the space heating efficiency by 25% in rated operating conditions.

An environment to support designers in the modeling, analysis and simulation of concurrent systems is described. It is shown how a fully nested structure model supports multilevel design and focuses attention on the interfaces between the modules which serve to encapsulate behavior. Using simple examples the paper indicates how a formal graph model can be used to model behavior in three domains: control flow, data flow, and interpretation. The effectiveness of the explicity environment model in SARA is discussed and the capability to analyze correctness and evaluate performance of a systemmodel are demonstrated. A description of the integral help designed into SARA shows how the designer can be offered consistent use of any new tool introduced to support the design process.

The Phase II system has been created with a series of hydraulic fracturing experiments at the Fenton Hill Hot Dry Rock site. Experiment 2032, the largest of the fracturing operations, involved injecting 5.6 million gallons (21,200m/sup 3/) of water into wellbore EE-2 over the period December 6-9, 1983. The experiment has been modeled using geothermal simulator FEHM developed at Los Alamos National Laboratory. The modeling effort has produced strong evidence of a large highly fractured reservoir. Two long term heat extraction schemes for the reservoir are studied with the model.

The Hydrogen Macro SystemModel (MSM) is a simulation tool that links existing and emerging hydrogen-related models to perform rapid, cross-cutting analysis. It allows analysis of the economics, primary energy-source requirements, and emissions of hydrogen production and delivery pathways.

and Lin Zhong Department of Electrical and Computer Engineering, Rice University 6100 Main St., TX 77005 for the great diversity in the hardware and usage of mobile systems. Moreover, existing system energy models intervals of at least 10 ms, or at a rate no lower than 100 Hz. Per-application energy accounting is useful

During the past six years, the Florida Solar Energy Center (FSEC) has conducted extensive experimental research on radiant barrier systems (RBS). This paper presents recent research on the development of mathematical attic models. Two levels of modeling capability have been developed. A very simplified model based on ASHRAE procedures in used to study the sensitivity of RBS performance parameters, and a very detailed finite element model is used to study highly complex phenomena, including moisture adsorption and desorption in attics. The speed of the simple model allows a large range of attic parameters to be studies quickly, and the finite element model provides a detailed understanding of combined heat and moisture transport in attics. This paper concentrates on a parametric analysis of attic RBS using the simplified model. The development of the model is described, and results of the parametric analyses are presented and discussed. Preliminary results from the finite element model are also compared with measurements from a test attic to illustrate the effects of moisture adsorption and desorption in common attics.

model or CIM classi- fies instances by considering the discrimination abil- ity of their features, which was proven to be useful for word sense disambiguation at SENSEVAL-1. But the CIM has a problem of information loss. KUNLP system at SENSEVAL-2 uses a modified version of the CIM for word sense disambiguation. We

Load management has been proposed as a means whereby an electric utility can reduce its requirements for additional generation, transmission, and distribution investments, shift fuel dependency from limited to more abundant energy resources, and improve the efficiency of the electric energy system. There exist, however, serious technological and economic questions which must be answered to define the cost trade-offs between initiating a load management strategy or adding additional capacity to meet the load. One aspect of this complex problem is to determine how the load profile might be modified by the load management option being considered. Towards this end, a model has been developed to determine how a power system with an active load control system should be operated to make the best use of its available resources. The model is capable of handling all types of conventional generating sources including thermal, hydro, and pumped storage units, and most appliances being considered for direct control including those with inherent or designed storage characteristics. The model uses a dynamic programming technique to determine the optimal operating strategy for a given set of conditions. The use of the model is demonstrated. Case study results indicate that the production cost savings that can be achieved through the use of direct load control are highly dependent on utility characteristics, load characteristics, storage capacity, and penetration. The load characteristics that produce the greatest savings are: large storage capacity; high coincidence with the system peak; large connected load per point; and moderately high diversity fraction.

In this paper we present a probabilistic P system simulator that implements the evolution-communication model proposed in (Cavaliere, 2003) enriched with some probabilistic parameters inspired by the cell biology. After describing the software and ... Keywords: bacteria, membrane computing, photosynthesis, probability, respiration, software

The methods developed by authors are applied to some reductions of BBGKY hierarchy, namely, various examples of Vlasov-like systems which are important both for fusion modeling and for particular physical problems related to plasma/beam physics. We mostly concentrate on phenomena of localization and pattern formation.

In this paper the normalized form of the generalized integral parabolic spline is described, which interpolates the integral averaged values of piecewise-smooth function. The three-dimensional system of partial differential equations as model of transport ... Keywords: conservative averaging, integral spline, layered media, three-dimensional, transport processes

In sociology, the role concept is deeply researched to predict activities of human organizations and theorized with many sub-theories. In the same direction, multi-agent system researchers use the role concept to model and program the agents behaviours, ...

Equilibrium climate sensitivity of the Community Climate SystemModel, version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient ...

Responsible, efficient and well-planned power consumption is becoming a necessity for monetary returns and scalability of computing infrastructures. While there are numerous sources from which power data can be obtained, analyzing this data is an intrinsically ... Keywords: Energy model, Grid'5000, distrbuted systems

The successful adoption of a strategic information system SIS is shown to hinge upon a favorable decision to develop a SIS and on a favorable decision to use the developed SIS. A model is exhibited that integrates the factors that lie behind these two ...

based design. This paper presents a development process based on modelling, simulation, and code synthesis. The DCharts formalism, a Statecharts variant with extensions, is used to model a small application to demonstrate our approach: a traffic light. The development of this system highlights the use of various formalisms with appropriate supporting tools: AToM 3, A Tool for Multi-formalism and Meta-Modelling, is used as a multi-formalism visual modelling environment; SVM is the simulation engine used to experiment with prototype models; SCC is the code synthesizer that generates reusable source code in a variety of target languages. Transformation onto the Communicating Sequential Processes (CSP) formalism allows for model checking using the Failures Divergences Refinement Checker (FDR2) model checker. We demonstrate how using multiple formalisms as well as model transformations during the design process can drastically improve productivity, reliability and reusability. 1. MODELLING, ANALYSIS AND SIMU-LATION BASED DESIGN Compared to traditional software programming, modelling and simulation based (software) design has many advantages. By modelling the structure and behaviour of the system at an appropriate level of abstraction in the most appropriate formalism(s), accidental complexity will be minimized, and the designer can focus on essential issues instead of being bogged down with implementation details at early stages in the development process. 1.1. The process Our modelling and simulation based design process is illustrated in Figure 1. The system designer starts from a set of requirements, which constrain the design space. In the example given here, the requirements are not modelled explicitly

Sample records for modeling system nems from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "modeling system nems" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

In a water distribution system from groundwater supply, the bulk of energy consumption is expended at pump stations. These pumps pressurize the water and transport it from the aquifer to the distribution system and to elevated storage tanks. Each pump in the system has a range of possible operating conditions with varying flow rates, hydraulic head imparted, and hydraulic efficiencies. In this research, the water distribution system of a mid-sized city in a subtropical climate is modeled and optimized in order to minimize the energy usage of its fourteen pumps. A simplified model of the pipes, pumps, and storage tanks is designed using freely-available EPANET hydraulic modeling software. Physical and operational parameters of this model are calibrated against five weeks of observed data using a genetic algorithm to predict storage tank volume given a forecasted system demand. Uncertainty analysis on the calibrated parameters is performed to assess model sensitivity. Finally, the pumping schedule for the system's fourteen pumps is optimized using a genetic algorithm in order to minimize total energy use across a 24-hour period.

APECS (Advanced Process Engineering Co-Simulator) is an integrated software suite that combines the power of process simulation with high-fidelity, computational fluid dynamics (CFD) for improved design, analysis, and optimization of process engineering systems. The APECS system uses commercial process simulation (e.g., Aspen Plus) and CFD (e.g., FLUENT) software integrated with the process-industry standard CAPE-OPEN (CO) interfaces. This breakthrough capability allows engineers to better understand and optimize the fluid mechanics that drive overall power plant performance and efficiency. The focus of this paper is the CAPE-OPEN complaint stochastic modeling and reduced order model computational capability around the APECS system. The usefulness of capabilities is illustrated with coal fired, gasification based, FutureGen power plant simulation. These capabilities are used to generate efficient reduced order models and optimizing model complexities.

We further develop a thermal LB model for multiphase flows. In the improved model, we propose to use the FFT scheme to calculate both the convection term and external force term. The usage of FFT scheme is detailed and analyzed. By using the FFT algorithm spatiotemporal discretization errors are decreased dramatically and the conservation of total energy is much better preserved. A direct consequence of the improvement is that the unphysical spurious velocities at the interfacial regions can be damped to neglectable scale. Together with the better conservation of total energy, the more accurate flow velocities lead to the more accurate temperature field which determines the dynamical and final states of the system. With the new model, the phase diagram of the liquid-vapor system obtained from simulation is more consistent with that from theoretical calculation. Very sharp interfaces can be achieved. The accuracy of simulation results are also verified by the Laplace law. The FFT scheme can be easily applied t...